Last-mile logistics of perishable products: a review of effectiveness and efficiency measures used in empirical research

Madelen Lagin (Department of Business, Dalarna University, Falun, Sweden)
Johan Håkansson (Department of Computer and Information Management, Dalarna University, Falun, Sweden)
Carin Nordström (Department of Material and Technology, Dalarna University, Falun, Sweden)
Roger G. Nyberg (Department of Computer and Information Management, Dalarna University, Falun, Sweden)
Christina Öberg (CTF Service Research Center, Karlstad University, Karlstad, Sweden) (Ratio Institute, Stockholm, Sweden)

International Journal of Retail & Distribution Management

ISSN: 0959-0552

Article publication date: 11 August 2022

Issue publication date: 19 December 2022

2390

Abstract

Purpose

Current online business development redistributes last-mile logistics (LML) from consumer to retailer and producer. This paper identifies how empirical LML research has used and defined logistic performance measures for key grocery industry actors. Using a multi-actor perspective on logistic performance, the authors discuss coordination issues important for optimising LML at system level.

Design/methodology/approach

A semi-systematic literature review of 85 publications was conducted to analyse performance measurements used for effectiveness and efficiency, and for which actors.

Findings

Few empirical LML studies exist examining coordination between key actors or on system level. Most studies focus on logistic performance measurements for retailers and/or consumers, not producers. Key goals and resource utilisations lack research, including all key actors and system-level coordination.

Research limitations/implications

Current LML performance research implies a risk for sub-optimisation. Through expanding on efficiency and effectiveness interplay at system level and introducing new research perspectives, the review highlights the need to revaluate single-actor, single-measurement studies.

Practical implications

No established scientific guidelines exist for solving LML optimisation in the grocery industry. For managers, it is important to thoroughly consider efficiency and effectiveness in LML execution, coordination and collaboration among key actors, avoiding sub-optimisations for business and sustainability.

Originality/value

The study contributes to current knowledge by reviewing empirical research on LML performance in the grocery sector, showing how previous research disregards the importance of multiple actors and coordination of actors, efficiency and effectiveness.

Keywords

Citation

Lagin, M., Håkansson, J., Nordström, C., Nyberg, R.G. and Öberg, C. (2022), "Last-mile logistics of perishable products: a review of effectiveness and efficiency measures used in empirical research", International Journal of Retail & Distribution Management, Vol. 50 No. 13, pp. 116-139. https://doi.org/10.1108/IJRDM-02-2021-0080

Publisher

:

Emerald Publishing Limited

Copyright © 2022, Madelen Lagin, Johan Håkansson, Carin Nordström, Roger G. Nyberg and Christina Öberg

License

Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode


Introduction

As with other retail sectors facing omni-channel logistic challenges (Bèzes, 2021; Jocevski et al., 2019; Kembro and Norrman, 2019), the increased demand and home deliveries of perishable products via online ordering has changed the retail supply chain in the grocery sector (Salhieh et al., 2021; Seghezzi and Mangiaracina, 2020; Xiao et al., 2018). This includes a shift in last-mile logistic (LML) costs and executions from consumers to retailers and, potentially, producers (Castillo et al., 2022; Melkonyan et al., 2020) and thereby an increased need to coordinate among actors (Bressolles and Lang, 2019; Kuhn and Sternbeck, 2013; Olsson et al., 2019). Coordination complexity increases with the number of actors, which dilutes the logistic performances measured (Belavina et al., 2017; Hübner et al., 2016) and highlights the importance of both efficiency and effectiveness of resource use and goal fulfilment for the actors to minimise sub-optimisations in the supply chain (Melkonyan et al., 2020; Salhieh et al., 2021).

This paper aims to identify how empirical research on LML has used and defined logistic performance measures for key grocery industry actors. We examine if, and how, previous LML empirical studies combine efficiency and effectiveness in relation to multiple actors in the grocery retail supply chain. By using a multi-actor perspective, we can discuss coordination issues that are important for optimising LML when it is transferred from consumers to retailers and producers. In doing so, we argue for the importance of considering a system-level perspective on LML. Based on limited findings related to our core search objective, we synthesise how efficiency and effectiveness have been studied in relation to single actors in the grocery sector while indicating avenues for future research.

The primary contribution of this paper is the identification of present perspectives on efficiency and effectiveness on LML. Over time, an increasing number of literature reviews on LML have been published. These focused directly on LML as a distribution structure based on the movement of products to consumers (Lim et al., 2018), concerned sustainability (He, 2020; Mangiaracina et al., 2015; Olsson et al., 2019), treated logistical issues as secondary or concerned non-perishable products (Bourlakis et al., 2008; Crainic et al., 2018; Delafenestre, 2019; Jain et al., 2017; Kannan and Li, 2017). None of these have captured multi-actor focus, coordination or system levels in the grocery sector combined with efficiency and effectiveness as two sides of the same coin. Our semi-systematic literature review adds to previous studies and contributes to a widening of LML research by reviewing past research focusing on actor(s), efficiency and effectiveness foci, enabling an updated research agenda and a broadening of current research perspectives.

Theoretical lens

To provide a theoretical background to our review, we introduce below the components of our argued ideal of a system level with logistics performance measures related to both effectiveness and efficiency.

Logistic performance: effectiveness and efficiency

In the logistics literature, efficiency and effectiveness have been identified through several measures, partly contingent on what actor is described. Examples of effectiveness measures are profit maximisation (Salhieh et al., 2021), service quality, market share, loyalty (Chow et al., 1994) and sustainability (Sallnäs and Björklund, 2020). Efficiency measures include optimised delivery costs (e.g. de Borba et al., 2020; Milioti et al., 2020; Paidi et al., 2020), product offer (Lim et al., 2018; Zondag et al., 2017), website costs and functions (Bèzes, 2021; Xing and Grant, 2006), production costs (Abushaikha et al., 2018; Shah and Khanzode, 2017; Zhang et al., 2019) and consumer relationship management (Zondag et al., 2017).

For the consumer, effectiveness measures are more likely related to purchase satisfaction (Cotarelo et al., 2021; Oeser et al., 2018; Sorkun et al., 2020). Efficiency measures are related to delivery costs (Hagberg and Holmberg, 2017; Xiao et al., 2018), product offer and costs (Jain et al., 2017), website functions (Kannan and Li, 2017) and attachment (Bouzaabia et al., 2013; Kumar and Anjaly, 2017).

While varying definitions and measures exist for logistic effectiveness and efficiency, the connection between the two can be understood as optimised resource utilisation (efficiency) in relation to goal achievement (effectiveness) (Fugate et al., 2010; Seghezzi and Mangiaracina, 2020). Including goals and resource utilisation provides an integrated framework (Bressolles and Lang, 2019; Elgazzar et al., 2019; Fernie et al., 2010), where different measures may contrast, or potentially reinforce, each other (Fugate et al., 2010).

Coordination and system level LML performance

An integrated framework including both efficiency and effectiveness is a first step towards grasping a more holistic view on LML. In addition, a multi-actor perspective would be vital as the grocery retail supply chain changes. A multi-actor perspective may either mean that actors are considered as contextual to each other (Bèzes, 2021; Cotarelo et al., 2021; Hübner et al., 2016), or how a system-level perspective is adopted (Crainic et al., 2018; Wiese et al., 2012).

Contextualisation includes how other parties or factors affect a focal firm's logistic efficiency and effectiveness and draws attention to coordination (Kumar et al., 2017; Mackelprang et al., 2014). Examples of contextual factors are supply-chain control (Fernie et al., 2010), consumer density (Belavina et al., 2017; He, 2020; Hübner et al., 2016) and product characteristics (Boyer et al., 2009). Boyer et al. (2009) argued that perishable product offerings may not be justified if the possibility of route planning flexibility does not exist. Contextualisation emphasises coordination from a single actor's point of view. In contrast to this, a holistic, system-level perspective (cf. Churchman, 1968 and those following his idea) means that multiple actors – consumers, retailers and producers – are considered simultaneously (Wiese et al., 2012) and is a rejuvenated perspective in logistics studies, not least when discussing sustainability (Öberg et al., 2012). The system level would emphasise optimisation for actors combined, rather than for individual parties, and would stress coordination for efficiency and effectiveness for the system. During times of change, a system-dynamics perspective enables the capturing of interplay among actors (Baporikar, 2020; Mingers and White, 2010) and their redistribution of tasks, responsibilities and performances. In the study of system dynamics, coordination would be raised as an issue affecting system-level performance, where, for instance, badly coordinated activities would lead to inefficient, non-optimised resource uses.

While it is most common to view logistics as a demand-driven process (Fernie et al., 2010), or possibly as a quantifiable part of a system (Mingers and White, 2010), logistic performance at the system level would need to take goal coordination into consideration. This means that the system-level approach to LML would explain how efficiency and effectiveness for producers, retailer and consumers combined become the consequence of trade-offs and coordination among the actors, argued in this paper as an ideal perspective to capture LML when the grocery retail supply chain changes.

Methods

Having noted the lack of past reviews on LML efficiency and effectiveness for multiple actors, our literature review focused on empirical (including empirical-based simulations and optimisation studies) publications related to LML, to analyse how effectiveness and efficiency were discussed, defined and measured for various actors, and for those actors combined.

Semi-systematic review

While previous reviews on LML have been bibliometric (e.g. Delafenestre, 2019), systematic (e.g. He, 2020), semi-structured/systematic (e.g. Mangiaracina et al., 2015), or unstructured (e.g. Bourlakis et al., 2008), we conducted a semi-systematic literature review that was open, adaptable and iterative (Tranfield et al., 2003), to allow for the inclusion of multidisciplinary contributions. Compared to other review methods, this approach concentrates on the content of articles and ensures that included publications have the intended focus through qualitative evaluations and directed searches.

Table 1 describes conducted searches, rationales and total articles reviewed. Using Google Scholar for initial searches provided the possibility to cover several different disciplines and allowed us to include books and chapters, while Web of Science helped to verify search results and analyse publications by using text-mining techniques. The following words functioned as keywords in our search string: e-commerce, delivery, business models and grocery, while -home electronics, -clothes, -furniture, -developing country, -law and -emerging markets functioned as exclusion commands.

A publication was considered eligible for inclusion (Rationale in Table 1) if the visible information contained one or more keywords, or concepts, broadly capturing an organisational setup of the e-commerce business model focusing on delivery (Belavina et al., 2017; Lim et al., 2018). From 1,000 publications, 70 publications were relevant for inclusion and of empirical nature. To verify the Google Scholar search (Halevi et al., 2017), we identified journals with the most published articles in the second search and the top-tier journals in the third search, leading to the inclusion of four, respectively zero, more articles. To ensure that no in-press articles were missed, a control search (fourth search) was conducted, which resulted in four additional articles.

Lastly, to ensure that the publications derived in the semi-systematic review process reflected our topic of focus, we compared these to the 500 most cited articles (fifth search) according to Web of Science. We used NVivo's word frequency query to identify the 1,000 most frequent words/concepts in article titles, abstracts and keywords in the respective set of articles. Word cloud visualisation (Figure 1) helped to determine the quality of the Google Scholar data and allowed identification of missing articles from our sample by timewise comparison. The word clouds indicated that our main sample was representative (also verified by how the reading of abstracts from the 500 articles only led to an additional seven articles for inclusion in our sample). With that said, grocery, as the sector of interest, was not well represented in the larger 500-article sample. This indicates that the targeted, semi-systematic search more effectively captured publications of interest. The clouds contain various actors, and to a lesser extent expression of efficiency and effectiveness measures, while not showing how authors used or combined these, thus leaving questions unanswered, which our content-based analysis answered.

Data analysis

As seen in Table 1, the selection process rendered 85 publications for review (see Appendix for the specific publications). We conducted a thematic analysis of the publications. Their methodological approaches were manually coded in NVivo (Figure 2). Then, we identified indicators of effectiveness and efficiency for individual or combined actors (see Table 2).

Next, we focused on potential trade-off situations of logistic performance measurements in terms of (1) performance measures themselves, (2) coordination among actors and (3) to what extent a system level was considered along the axes of measures and/or actors. This helped us identify research gaps for effectiveness and efficiency, as well as actors or actor combinations, in line with our proposed system-level perspective including all actors, efficiency and effectiveness.

Findings

Methods used in the reviewed publications

Figure 2 presents the methodological approaches and data collection methods used in the 85 publications. The three most used approaches are (1) optimisation studies applying a combination of secondary data and qualified estimations, (2) surveys and (3) case studies. For case studies interviews and secondary data dominated qualitative data collections, while optimisation dominated the quantitative case studies (see diagram to the right in Figure 2).

Performance measurements used by key actors in LML

Table 3 presents the findings from the thematic review.

Table 3 shows that there were a limited number of publications focusing on both effectiveness and efficiency and that these were dominated by a single-actor focus. A multi-actor perspective only applied in two life-cycle assessment studies dealing with sustainability. Only a few publications took into consideration several logistic performance measurements simultaneously for retailers or consumers, while producers remained rare.

As for effectiveness, no publications considered the producer, and in the studies on retailers or consumers, multiple actors' effectiveness was not considered, nor was coordination of goals among actors.

Considerably more studies focused on efficiency, dominated by assumptions of resource utilisation for retailers or consumers. Only one empirical study focused on the local food producer's efficiency measures, but did not consider coordination between actors, despite the raised benefits for producers in joining forces with other actors. Using multiple efficiency measures was more common for consumers than retailers. Only one publication (Boyer and Hult, 2005) covered multiple actors while adopting several efficiency measures. They connected consumers to the operational resources that retailers used to create an online purchasing context, including how direct store-based delivery led to high delivery costs, low picking efficiency, low capital investments and high consumer convenience. Indirect distribution-centre delivery was described as leading to low delivery costs, high picking efficiency, high capital investments and low consumer convenience. Although Boyer and Hult (2005) did not single out LML, their study indicated how trade-offs are necessary in terms of operational variability and resource utilisation in relation to order fulfilment and delivery, thereby indicating different LML efficiency solutions at the system level. Figure 3 highlights the reviewed publications performance measure and actor focus.

With the domination of single-actor, single-measure perspectives and the retailer's efficiency being the most frequent focus, we raise three plausible explanations for this. Firstly, research has implicitly viewed LML as a problem within the retailer's boundaries, with focus on the resource utilisation for delivery and production (see Table 3 Efficiency). In the reviewed publications, this is done by assuming that the retailer handles the LML as inbound transportation and decides about the product assortment, which could explain the continuing assumption that the retailer carries extensive expenses for LML (e.g. Kuhn and Sternbeck, 2013).

Secondly, viewing LML as a transfer cost has implicitly led to the assumptions that it can be separately quantifiable from other LML issues and actors, such as relationships or website configurations. This separation is also visible in the few articles that use several efficiency measures, or when effectiveness and efficiency are considered simultaneously. It is not until more recent sustainability studies that a system level of both efficiency and effectiveness is adopted to capture the complexity of consequences and the boundary-spanning effects on the environment (see Table 3 Effectiveness and efficiency). However, the focus has been on environmental efficiency for the sake of society rather than considering coordination of activities at the system level.

The third explanation relates to methodology. Applying methods weighted towards quantitative measurements (see Figure 2) results in the reviewed studies focusing on the operationalisation of separate measures, and normally this requires the researcher to disregard coordination issues or multiple actors as primary informants. This is also the case even when a more complex approach to the efficiency of LML is used, since it is common to treat the other parties as secondary to the retailer's task to optimise LML.

Concluding discussion

This study identified how empirical research on LML has used and defined performance measures for key grocery industry actors. With past single-actor, single-measures, there are risks of leaving parties out, disregarding consequences and sub-optimising LML, especially as the development includes a redistribution of tasks along the grocery retail supply chain. To achieve efficient and effective LML under new market conditions, optimisation would follow from system-level coordination among, rather than for, individual actors.

Fugate et al. (2010) have previously argued for the need to simultaneously consider efficiency and effectiveness in logistics, and sustainability studies have started to address system-level responsibilities and consequences of logistics (e.g. Öberg et al., 2012; Sallnäs and Björklund, 2020), while activities distributed and redistributed among parties would also have system-level business effects. A system perspective would place multiple actors' goal and resource coordination in focus, a subject that does not seem to have been investigated empirically in previous LML research. This would require collaboration among actors in the grocery retail supply chain to ensure that goods, for instance, are delivered on time, that waste is curtailed and that costs and transport are minimised on the system level. This collaboration would focus on questions regarding who does what and how activities and risks distributed among parties are compensated by others.

Logistic network optimisation studies may fuel ideas related to efficiency, while Fugate et al. (2010) could help to expand and combine across efficiency and effectiveness measures at the system level. Tools, such as agent-based modelling, location analyses, cause-and-effect diagrams and multi-objective techniques, may help to achieve the system-level efficiency and effectiveness. The multi-actor perspective would generally include two considerations: (1) the aggregated efficient use of resources on the system level and (2) the measure of frictionless coordination and goal-alignment among parties. Measures of coordination would depart from the relationships among parties (e.g. relationship effectiveness and efficiency) rather than the actors themselves, while the system level would emphasise shared risk schemes, return transports to minimise total distances and measure filling rates across the supply chain.

Illustratively, Figure 4 depicts coordination of resources used for deliveries aiming at minimising empty transports and achieving profitability. The coordination means that it is through the relationships among actors that it is possible to discuss a potential redistribution of activities, who is responsible for what and how deliveries should be pursued (between what actors and, on the broader system level, in relation to other producers, retailers and consumers). This is accomplished by connecting the firms' individual operations to each other, the balancing of, for instance, the price among actors to achieve system level profitability combined with consumer satisfaction.

The figure depicts how coordination deals with both efficiency and effectiveness where such measures are transferred from the individual actors to efficiency and effectiveness in the coordination of actors (arrows in Figure 4) and thereby how goals and resource utilisation at the system level can reinforce each other. Trust, loyalty and information aesthetics would play a vital part here to determine the efficiency at the system level, since those measurements can be considered as relational goals and resource utilisation. Meanwhile, system-level measures would concern the optimal, aggregated resource use alone, as there is no (individual) actor's interest that represents the system level. The dilemma of setting boundaries, though, is delicate in practice and includes coordination with additional producers, retailers and consumers in the planning and execution of LML. Challenges further include the use of factual logistical data with customer data, since the latter is often of perceptual nature and needs to be transformed or merged to function as if it were logistical data.

A research agenda

Our literature review shows a need for more empirical evaluations of LML performance in the grocery sector using system-level analysis to determine LML performance, i.e. the function's effectiveness and efficiency. We therefore suggest the following avenues for future research:

LML system-level studies

The single-actor perspective dominating across research on efficiency and/or effectiveness for LML fails to cover the logic of LML. As a result, and as our main point in this paper, coordination of resources and goals is essential to consider in future empirical research. Such research should reach beyond contextualising other parties to a focal firm (e.g. Chhetri et al., 2017; He, 2020; Hübner et al., 2016) and empirically investigate coordination on system levels, as well as how efficiency and effectiveness are affected by the redistribution of activities, how coordination is best achieved and how activities should ideally be distributed across the system. This is also in line with the increased sustainability focus, while including additional efficiency and effectiveness measures. Designing LML research as multiple case studies, or comparative studies, would provide a means of viewing LML performance from multiple perspectives, based on various types of data, while exploring additional performance measures related to said perspectives. Such studies are essential since the conceptualisation of logistic performance is heterogenic, as is the conceptualisation of LML.

Producer and relationship inclusion

The demonstrated lack of research, including the producer's perspective, creates a limitation that hinders the conceptualisation of coordination and redistribution of activities at the system level. The producer's perspective should be included in proposed future research on multi-actor system LML studies, specifically due to the shift in LML cost and execution related to online operations. Additionally, while the retailer's relationship to consumers is of essential focus in other research streams (e.g. general e-commerce), it does not seem to have been a focus in LML research. Hence, we propose studies that integrate a system-level perspective with in-depth studies on producers and coordination between producer, retailer and consumer. This would help to establish the resource usage connected to LML efficiency, with specific focus on how relationships can work as a coordinating resource within a system.

Web resource utilisation for online business

Going further into detail on resource usage and its relation to online business, research on website costs and functions beyond consumers is limited (e.g. Faraoni et al., 2019; Weber and Badenhorst-Weiss, 2018). While consumers are interested in the functionality of the web, the actual platform resources (financial and operational) are most likely invested in by the other actors in the system. It is thereby of interest to further compare and analyse how web efficiency for LML can be coordinated to achieve both consumer satisfaction and profit maximisation. Here, COVID-19 has amplified web solutions and home delivery, while the gig economy has introduced new players to LML, allowing for opportunities to study web resource utilisation among actors.

Perishable product particularities

Perishable products may be damaged and therefore difficult for consumers to return, hence influencing both satisfaction and profit. As a result, coordination among actors would be assumed to be more demanding than for other types of products. Studies focusing specifically on perishable products and coordination among actors would be desirable, not least since consumers move away from being a main actor in LML and since perishable-product LML are vulnerable to temperature and timing, which means that additional items need to be included in any LML analysis.

By forwarding a system-level perspective when reviewing research, including both efficiency and effectiveness to better capture LML when multiple actors are involved and the distribution of tasks become unclear, this paper contributes to past research by indicating research gaps and important directions for future research. The study adds to past reviews on LML, creating ground for future studies to extend present knowledge on LML and highlighting how research and practice may potentially have become increasingly detached regarding the LML scope in the grocery sector.

Figures

Word cloud: Based on 500 most cited in Web of Science (left) and our sample (right)

Figure 1

Word cloud: Based on 500 most cited in Web of Science (left) and our sample (right)

Methods and data collection in reviewed articles (85). Multiple methods and data may apply to the individual articles

Figure 2

Methods and data collection in reviewed articles (85). Multiple methods and data may apply to the individual articles

Visualisation of the usage of effectiveness and efficiency measurements in the reviewed literature

Figure 3

Visualisation of the usage of effectiveness and efficiency measurements in the reviewed literature

Suggested illustration of LML performance at the system-level, given reviewed literature

Figure 4

Suggested illustration of LML performance at the system-level, given reviewed literature

Review selection process and rationales

StepProcessRationaleNumber of publications included for review (n = 85)
Inclusion
1st searchTitle and first three rows in Google ScholarUsed keywords and concepts: food, omni-channel, digital supply, last mile, click and collect, distribution, local produce, independent, logistics, rural, urban, business-to-business, business-to-consumer and supply chain. Patents and citations were disabled. The words were used to select articles for further classification, while the concepts were considered complementary to the keywords or part of the keywords70
Using Google Scholar for initial searches provided the possibility to cover several different disciplines and allowed us to include books and chapters
Search dateMay 25, 2019, ≈24,100 articles in Google Scholar, where the first 1,000 publications, sorted by relevance, were screened for potential inclusion. A total of 167 publications screened for full inclusion
2nd searchIdentification of frequently used journalsJournals with more than four articles on the topic were searched again. Most articles from the first selection were published in the International Journal of Retail & Distribution Management (11 articles), International Journal of Physical Distribution and Logistics Management (10), Industrial Management and Data Systems (6), International Journal of Electronic Commerce (6), Journal of Operation Management (5) and Sustainability (4). The same search string was used in the specified journals
Added articles: Colla and Lapoule, 2012; Eriksson et al., 2019; Huang and Oppewal, 2006; Ring and Tigert 2001
4
Search dateFebruary 6, 2020, using the same search string and the same inclusion eligibilities as in the first search
3rd searchStrategic choice of journalsThe topic is efficiency and effectiveness issues pertaining primarily to logistics, supply chain, business and consumer logic. Articles in the previous steps fall under Academic Journal Quality Guide (AJG) categories of Marketing (14 journals, six of grade three or four), Operations, technology and management (13, seven of grade three or four), Information management (10, five of grade three) and General management (7, three of grade three or four). Most of the articles in previous steps are of a practical nature, and all grade four journals were searched in General management (seven journals), Information management (two journals) and Marketing (five journals). These journals provide theoretical and practical studies of high quality, and the AJG is relatively stable in its rankings (Morris et al., 2009). In the category of operations, technology and management, one journal is ranked level four according to AJG (Journal of Operations Management). The same search string was used
Added articles: none
0
Search dateFebruary 6, 2020, using the same search string and the same inclusion eligibilities as in the first search
4th searchIdentifying in-press articlesAt the end of the analytical process, we searched Google Scholar to identify in-press articles. The same search string and inclusion/exclusion criteria as in the 1st search were used for a time interval between 2020 and 2021 Jan
Added articles: Hillen and Fedoseeva, 2021; Liu et al., 2020; Pelet et al., 2020; Zhu et al., 2021
4
Search dateFebruary 9, 2021, using the same search string and the same inclusion eligibilities as in the first search
5th searchComparison of 500 most cited articlesWeb of Science helped to verify search results and analyse publications by using text-mining techniques. To ensure that our dataset captured our intended focus, we used the same search string in Web of Science to identify the 500 most cited articles to compare with through text-mining illustration and excluded redundant subject areas, such as microbiology and surgery
Through reading abstracts on those articles from the Web of Science search for years with the largest discrepancy in number of articles between the samples (2018-2020), we found an additional seven articles that we included in our further analysis
Added articles: Chen et al., 2020; Gee et al., 2019; Heard et al., 2019; Rai et al., 2019; Sousa et al., 2020; Vazquez-Noguerol et al., 2020; Wang et al., 2020
7
Exclusion
1st searchQuality of journal or bookArticles or books required to be ranked on at least two of three rankings: AJG/ABS 2018, Norwegian List, or Scimago. This allowed us to exclude research of low quality, regardless of discipline
LanguageOnly articles or books written in English to avoid translations
Topic out of scope for LML and groceryExamples of areas with a focus on, e.g. other type of products, previous literature
Type of publicationsPublications in the form of editorial summaries, working papers, or similar, are excluded as they failed to meet the review standards
Total number of reviewed publications85

Example of thematic analysis

MeasurementIndicator (examples)
Effectiveness*Profit maximisationRevenue/pricing strategy, business value creation, market size, sale ratio, availability of KPI
Consumer purchase satisfactionTime saving, physical ease, convenience, price, product offer
Market shareCompetition
Service qualityPossibility for returns, consumer services, total offer quality
SustainabilityEconomic feasibility, energy use, resource usage, material usage, social compliance
EfficiencyDelivery costsDelivery time, delivery distance, delivery quality, service quality, price for delivery, market density, missed deliveries, number of returns, security, route planning
Production costCompetition, price, warehouse cost, order system, economies of scale, production automation, digitalisation
Web designLayout, functionality, attractiveness, purchase security
Product offerProduct characteristics, availability, product differentiation, food waste
RelationshipsTrust, loyalty, opportunism, information aesthetics, corporate alliances

Note(s): While it would be reasonable to assume that profit maximisation and consumer purchase satisfaction are two parts of the same goal, it is equally reasonable to assume that consumers would not consider goals related to, e.g. market share or profit maximisation, or resource utilisation regarding, e.g. production costs

Result of studies using effectiveness and efficiency measurements by actor

Reviewed articles

JournalArticles
African Journal of Science, Technology, Innovation and Development
  1. Weber, A.N. and Badenhorst-Weiss, J.A. (2018), “The ‘new’ bricks-and-mortar store: An evaluation of website quality of online grocery retailers in BRICS countries”, African Journal of Science, Technology, Innovation and Development, Vol. 10 No. 1, pp.85-97. https://doi.org/10.1080/20421338.2017.1394957

Annals of Operations Research
  1. Wei, C., Asian, S., Ertek, G. and Hu, Z.H. (2018), “Location-based pricing and channel selection in a supply chain: A case study from the food retail industry”, Annals of Operations Research, Vol. 291, pp.1-26. https://doi.org/10.1007/s10479-018-3040-7

Asia Pacific Journal of Marketing and Logistics
  1. Liu, X., Tang, O. and Huang, P. (2008), “Dynamic pricing and ordering decision for the perishable food of the supermarket using RFID technology”, Asia Pacific Journal of Marketing and Logistics, Vol. 20 No. 1, pp.7-22. https://doi.org/10.1108/13555850810844841

  1. Wong, E., Tai, A.H., Wei, Y. and Yip, I. (2018), “Redesigning one-warehouse n-retailer routing model in inter-store stock transfer operations of an international retail chain distribution”, Asia Pacific Journal of Marketing and Logistics, Vol. 30 No. 3, pp.536-554. https://doi.org/10.1108/APJML-06-2017-0124

British Food Journal
  1. Faraoni, M., Rialti, R., Zollo, L. and Pellicelli, A.C. (2019), “Exploring e-loyalty antecedents in B2C e-commerce”, British Food Journal, Vol. 121 No. 2, pp.574-589. https://doi.org/10.1108/BFJ-04-2018-0216

  1. Wang, O., Somogyi, S. and Charlebois, S. (2020). "Food choice in the e-commerce era: A comparison between business-to-consumer (B2C), online-to-offline (O2O) and new retail", British Food Journal, Vol. 122 No. 4, pp.1215-37. https://doi.org/10.1108/bfj-09-2019-0682

Business Horizons
  1. Sousa, R., Horta, C., Ribeiro, R. and Rabinovich, E. (2020), "How to serve online consumers in rural markets: Evidence-based recommendations", Business Horizons, Vol. 63 No. 3, pp.351-62. https://doi.org/10.1016/j.bushor.2020.01.007

California Management Review
  1. Wolfinbarger, M. and Gilly, M.C. (2001), “Shopping online for freedom, control, and fun”, California Management Review, Vol. 43 No. 2, pp.34-55. https://doi.org/10.2307/41166074

Central European Journal of Operations Research
  1. Vazquez-Noguerol, M., Comesana-Benavides, J., Poler, R. and Prado-Prado, J. C. (2020) “An optimisation approach for the e-grocery order picking and delivery problem”, Central European Journal of Operations Research, pp.1-30. https://doi.org/10.1007/s10100-020-00710-9

Cogent Business and Management
  1. Mkansi, M., Eresia-Eke, C. and Emmanuel-Ebikake, O. (2018), “E-grocery challenges and remedies: Global market leaders perspective”, Cogent Business and Management, Vol. 5 No. 1, pp.1459338. https://doi.org/10.1080/23311975.2018.1459338

Communications of the Association for Information Systems
  1. Palmer, J., Kallio, J., Saarinen, T., Tinnila, M., Tuunainen, V.K. and van Heck, E. (2000), “Online grocery shopping around the world: Examples of key business models”, Communications of the Association for Information Systems, Vol. 4 No. 1, pp.1-44. https://doi.org/10.17705/1CAIS.00403

Computers & Industrial Engineering
  1. Faugère, L. and Montreuil, B. (2020), “Smart locker bank design optimization for urban omnichannel logistics: Assessing monolithic vs. modular configurations”, Computers & Industrial Engineering, vol. 139, 105544. https://doi.org/10.1016/j.cie.2018.11.054

Computers and Operations Research
  1. Emeç, U., Çatay, B. and Bozkaya, B. (2016), “An adaptive large neighborhood search for an e-grocery delivery routing problem”, Computers and Operations Research, Vol. 69 May, pp.109-125. https://doi.org/10.1016/j.cor.2015.11.008

Decision Sciences
  1. Xiao, Y. and Chen, J. (2012), “Supply chain management of fresh products with producer transportation”, Decision Sciences, Vol. 43 No. 5, pp.785-815. https://doi.org/10.1111/j.1540-5915.2012.00375.x

Environment and Planning A: Economy and Space
  1. Murphy, A.J. (2003), “(Re)solving space and time: Fulfilment issues in online grocery retailing”, Environment and Planning A: Economy and Space, Vol. 35 No. 7, pp.1173-1200. https://doi.org/10.1068/a35102

European Journal of Operational Research
  1. Asdemir, K., Jacob, V.S. and Krishnan, R. (2009), “Dynamic pricing of multiple home delivery options”, European Journal of Operational Research, Vol. 196 No. 1, pp.246–257. https://doi.org/10.1016/j.ejor.2008.03.005

  1. Zhu, S., Hu, X., Huang, K. and Yuan, Y. (2021), “Optimization of product category allocation in multiple warehouses to minimize splitting of online supermarket customer orders”, European Journal of Operational Research, Vol. 290 No. 2, pp.556-571. https://doi.org/10.1016/j.ejor.2020.08.024

European Management Journal
  1. Dussart, C. (2000), “Internet: The one-plus-eightre-volutions'”, European Management Journal, Vol. 18 No. 4, pp.386-397. https://doi.org/10.1016/S0263-2373(00)00028-1

  1. Verona, G. and Prandelli, E. (2002), “A dynamic model of customer loyalty to sustain competitive advantage on the web”, European Management Journal, Vol. 20 No. 3, pp.299-309. https://doi.org/10.1016/S0263-2373(02)00046-4

  1. Zott, C., Amit, R. and Donlevy, J. (2000), “Strategies for value creation in e-commerce: Best practice in Europe”, European Management Journal, Vol. 18 No. 5, pp.463-475. https://doi.org/10.1016/S0263-2373(00)00036-0

European Transport Research Review
  1. Arnold, F., Cardenas, I., Sörensen, K. and Dewulf, W. (2018), “Simulation of B2C e-commerce distribution in Antwerp using cargo bikes and delivery points”, European Transport Research Review, Vol. 10 No. 2, pp.1-13. https://doi.org/10.1007/s12544-017-0272-6

Industrial Management and Data Systems
  1. Lunce, S.E., Lunce, L.M., Kawai, Y. and Maniam, B. (2006), “Success and failure of pure-play organizations: Webvan versus Peapod, a comparative analysis”, Industrial Management and Data Systems, Vol. 106 No. 9, pp.1344-1358. https://doi.org/10.1108/02635570610712618

  1. Ogawara, S., Chen, J.C. and Zhang, Q. (2003), “Internet grocery business in Japan: Current business models and future trends”, Industrial Management and Data Systems, Vol. 103 No. 9, pp.727-735. https://doi.org/10.1108/02635570310506142

  1. Pan, S., Giannikas, V., Han, Y., Grover-Silva, E. and Qiao, B. (2017), “Using customer-related data to enhance e-grocery home delivery”, Industrial Management and Data Systems, Vol. 117 No. 9, pp.1917-1933. https://doi.org/10.1108/IMDS-10-2016-0432

  1. San-Martín, S. and Jimenez, N. (2017), “Curbing electronic shopper perceived opportunism and encouraging trust”, Industrial Management and Data Systems, Vol. 117 No. 10, pp.2210-2226. https://doi.org/10.1108/IMDS-08-2016-0315

Information Systems and e-Business Management
  1. Plant, R., Willcocks, L. and Olson, N. (2003), “Measuring e-business performance: Towards a revised balanced scorecard approach”, Information Systems and e-Business Management, Vol. 1 No. 3, pp.265-281. https://doi.org/10.1007/s10257-003-0015-1

Integrated Manufacturing Systems
  1. Boyer, K.K., Hult, G.T. and Frohlich, M. (2003), “An exploratory analysis of extended grocery supply chain operations and home delivery”, Integrated Manufacturing Systems, Vol. 14 No. 8, pp.652-663. https://doi.org/10.1108/09576060310503465

International Journal of Electronic Commerce
  1. Cao, L. (2014), “Business model transformation in moving to a cross-channel retail strategy: A case study”, International Journal of Electronic Commerce, Vol. 18 No. 4, pp.69-96. https://doi.org/10.2753/JEC1086-4415180403

  1. Lewis, J., Whysall, P. and Foster, C. (2014), “Drivers and technology-related obstacles in moving to multichannel retailing”, International Journal of Electronic Commerce, Vol. 18 No. 4, pp.43-68. https://doi.org/10.2753/JEC1086-4415180402

  1. Steinfield, C., Bouwman, H. and Adelaar, T. (2002), “The dynamics of click-and-mortar electronic commerce: Opportunities and management strategies”, International Journal of Electronic Commerce, Vol. 7 No. 1, pp.93-119. https://doi.org/10.1080/10864415.2002.11044254

International Journal of Engineering Business Management
  1. Ghezzi, A., Mangiaracina, R. and Perego, A. (2012), “Shaping the e-commerce logistics strategy: A decision framework”, International Journal of Engineering Business Management, Vol. 4 No. 13, pp.4-13. https://doi.org/10.5772/51647

  1. Stritto, G.D. and Schiraldi, M. (2013), “A strategy oriented framework for food and beverage e-supply chain management”, International Journal of Engineering Business Management, Vol. 5 No. 50, pp.1-12. https://doi.org/10.5772/57167

International Journal of Hospitality Management
  1. Cho, M., Bonn, M.A. and Li, J.J. (2019), “Differences in perceptions about food delivery apps between single-person and multi-person households”, International Journal of Hospitality Management, Vol. 77 January, pp.108-116. https://doi.org/10.1016/j.ijhm.2018.06.019

International Journal of Information Management
  1. Thornton, J. and Marche, S. (2003), “Sorting through the dot bomb rubble: How did the high-profile e-tailers fail?”, International Journal of Information Management, Vol. 23 No. 2, pp.121-138. https://doi.org/10.1016/S0268-4012(02)00104-4

International Journal of Logistics: Research and Applications
  1. Mason, R. and Lalwani, C. (2007), “Transport integration tools for supply chain management”, International Journal of Logistics: Research and Applications, Vol. 9 No. 1, pp.57-74. https://doi.org/10.1080/13675560500534599

International Journal of Operations & Production Management
  1. Adebanjo, D., Kehoe, D., Galligan, P. and Mahoney, F. (2006), “Overcoming the barriers to e cluster development in a low product complexity business sector”, International Journal of Operations and Production Management, Vol. 26 No. 8, pp.924-939. https://doi.org/10.1108/01443570610678675

  1. Starr, M.K. (2003), “Application of POM to e-business: B2C e-shopping”, International Journal of Operations and Production Management, Vol. 23 No. 1, pp.105-124. https://doi.org/10.1108/01443570310453280

International Journal of Physical Distribution & Logistics Management
  1. Kämäräinen, V., Saranen, J. and Holmström, J. (2001a), “The reception box impact on home delivery efficiency in the e-grocery business”, International Journal of Physical Distribution and Logistics Management, Vol. 31 No. 6, pp.414-426. https://doi.org/10.1108/09600030110399414

  1. Rai, H. B., Verlinde, S., Macharis, C., Schoutteet, P. and Vanhaverbeke, L. (2019), “Logistics outsourcing in omnichannel retail: State of practice and service recommendations”, International Journal of Physical Distribution & Logistics Management, Vol. 49 No. 3, pp.267-86. https://doi.org/10.1108/ijpdlm-02-2018-0092

  1. Yrjölä, H. (2001), “Physical distribution considerations for electronic grocery shopping”, International Journal of Physical Distribution and Logistics Management, Vol. 31 No. 10, pp.746-761. https://doi.org/10.1108/09600030110411419

International Journal of Production Research
  1. Deutsch, Y. and Golany, B. (2018), “A parcel locker network as a solution to the logistics last mile problem”, International Journal of Production Research, Vol. 56 No. 1-2, pp.251-261. https://doi.org/10.1080/00207543.2017.1395490

International Journal of Retail & Distribution Management
  1. Anckar, B., Walden, P. and Jelassi, T. (2002), “Creating customer value in online grocery shopping”, International Journal of Retail & Distribution Management, Vol. 30 No. 4, pp.211-220. https://doi.org/10.1108/09590550210423681

  1. Bressolles, G., Durrieu, F. and Deans, K.R. (2015), “An examination of the online service-profit chain”, International Journal of Retail & Distribution Management, Vol. 43 No. 8, pp.727-751. https://doi.org/10.1108/IJRDM-11-2013-0214

  1. Chhetri, P., Kam, B., Lau, K.H., Corbitt, B. and Cheong, F. (2017), “Improving service responsiveness and delivery efficiency of retail networks”, International Journal of Retail & Distribution Management, Vol. 45 No. 3, pp.271-291. https://doi.org/10.1108/IJRDM-07-2016-0117

  1. Colla, E. and Lapoule, P. (2012), “E-commerce: Exploring the critical success factors”, International Journal of Retail & Distribution Management, Vol. 40 No. 11, pp.842-864. https://doi.org/10.1108/09590551211267601

  1. Davies, A., Dolega, L. and Arribas-Bel, D. (2019), “Buy online collect in-store: Exploring grocery click and collect using a national case study”, International Journal of Retail & Distribution Management, Vol. 47 No. 3, pp.278-291. https://doi.org/10.1108/IJRDM-01-2018-0025

  1. Doherty, N.F., Ellis–Chadwick, F., Hackney, R. Grant, K. and Birtwistle, G. (2006), “The UK grocery business: Towards a sustainable model for virtual markets”, International Journal of Retail & Distribution Management, Vol. 34 No. 4/5, pp.354-368. https://doi.org/10.1108/09590550610660279

  1. Eriksson, E., Norrman, A. and Kembro, J. (2019), “Contextual adaptation of omni-channel grocery retailers' online fulfilment centers”, International Journal of Retail & Distribution Management, Vol. 47 No. 12, pp.1232-1250. https://doi.org/10.1108/IJRDM-08-2018-0182

  1. Huang, Y. and Oppewal, H. (2006), “Why consumers hesitate to shop online: An experimental choice analysis of grocery shopping and the role of delivery fees”, International Journal of Retail & Distribution Management, Vol. 34 No. 4, pp.334-353. https://doi.org/10.1108/09590550610660260

  1. Hübner, A.H., Kuhn, H., Wollenburg, J., Towers, N. and Kotzab, H. (2016b), “Last mile fulfilment and distribution in omni-channel grocery retailing: A strategic planning framework”, International Journal of Retail & Distribution Management, Vol. 44 No. 3, pp.228-247. https://doi.org/10.1108/IJRDM-11-2014-0154

  1. Kämäräinen, V., Småros, J., Jaakola, T. and Holmström, J. (2001b), “Cost-effectiveness in the e-grocery business”, International Journal of Retail & Distribution Management, Vol. 29 No. 1, pp.41-48. https://doi.org/10.1108/09590550110366352

  1. Lim, H., Widdows, R. and Hooker, N.H. (2009), “Web content analysis of e-grocery retailers: A longitudinal study”, International Journal of Retail & Distribution Management, Vol. 37 No. 10, pp.839-851. https://doi.org/10.1108/09590550910988020

  1. Morganosky, M. and Cude, B. (2002), “Consumer demand for online food retailing: Is it really a supply side issue?”, International Journal of Retail & Distribution Management, Vol. 30 No. 10, pp.451-458. https://doi.org/10.1108/09590550210445326

  1. Ring, L.J. and Tigert, D.J. (2001), “Viewpoint: The decline and fall of Internet grocery retailers”, International Journal of Retail & Distribution Management, Vol. 29 No. 6, pp.264-271. https://doi.org/10.1108/09590550110393956

Journal of the Academy of Marketing Science
  1. Mahar, S., Wright, P. D., Bretthauer, K. M. and Hill, R. P. (2014), “Optimizing marketer costs and consumer benefits across ‘clicks’ and ‘bricks’”, Journal of the Academy of Marketing Science, Vol. 42 No. 6, pp.619-641. https://doi.org/10.1007/s11747-014-0367-8

Journal of Business Economics and Management
  1. Seitz, C., Pokrivčák, J., Tóth, M. and Plevný, M. (2017), “Online grocery retailing in Germany: An explorative analysis”, Journal of Business Economics and Management, Vol. 18 No. 6, pp.1243-1263. https://doi.org/10.3846/16111699.2017.1410218

Journal of Business & Industrial Marketing
  1. Kotzab, H. (1999), “Improving supply chain performance by efficient consumer response? A critical comparison of existing ECR approaches”, Journal of Business and Industrial Marketing, Vol. 14 No. 5/6, pp.364-377. https://doi.org/10.1108/08858629910290111

Journal of Business Research
  1. Hillen, J. and Fedoseeva, S. (2021), “E-commerce and the end of price rigidity?”, Journal of Business Research, Vol. 125 March, pp.63-73. https://doi.org/10.1016/j.jbusres.2020.11.052

Journal of Cleaner Production
  1. Chen, J. M., Dan, B. and J. Shi, J. (2020), “A variable neighborhood search approach for the multi-compartment vehicle routing problem with time windows considering carbon emission”, Journal of Cleaner Production, Vol. 277., pp.1-14. https://doi.org/10.1016/j.jclepro.2020.123932

  1. Gee, I. M., Davidson, F. T., Speetles, B. L. and Webber, M. E. (2019), “Deliver me from food waste: Model framework for comparing the energy use of meal-kit delivery and groceries”, Journal of Cleaner Production, Vol. 236, pp.1-11. https://doi.org/10.1016/j.jclepro.2019.07.062

Journal of Global Information Technology Management
  1. Burn, J. and Barnett, M. (2000), “Emerging virtual models for global e-commerce - World wide eetailing in the e-grocery business”, Journal of Global Information Technology Management, Vol. 3 No. 1, pp.18-32. https://doi.org/10.1080/1097198X.2000.10856270

Journal of Intelligent Manufacturing
  1. Seok, H. and Nof, S.Y. (2018), “Intelligent information sharing among manufacturers in supply networks: Supplier selection case”, Journal of Intelligent Manufacturing, Vol. 29 No. 5, pp.1097-1113. https://doi.org/10.1007/s10845-015-1159-9

Journal of Management Information Systems
  1. Roberts, N., Campbell, D.E. and Vijayasarathy, L.R. (2016), “Using information systems to sense opportunities for innovation: Integrating postadoptive use behaviors with the dynamic managerial capability perspective”, Journal of Management Information Systems, Vol. 33 No. 1, pp.45-69. https://doi.org/10.1080/07421222.2016.1172452

Journal of Marketing Management
  1. Cui, G. and Wang, Y. (2010), “Consumers' SKU choices in an online supermarket: A latent class approach”, Journal of Marketing Management, Vol. 26 No. 5-6, pp.495-514. https://doi.org/10.1080/02672570903534704

  1. Gounaris, S., Dimitriadis, S. and Stathakopoulos, V. (2005), “Antecedents of perceived quality in the context of Internet retail stores”, Journal of Marketing Management, Vol. 21 No. 7-8, pp.669-700. https://doi.org/10.1362/026725705774538390

Journal of Organizational Computing and Electronic Commerce
  1. Picoto, W.N., Bélanger, F. and Palma-dos Reis, A. (2013), “M-Business organizational benefits and value: A qualitative study”, Journal of Organizational Computing and Electronic Commerce, Vol. 23 No. 4, pp.287-324. https://doi.org/10.1080/10919392.2013.837789

Journal of Operations Management
  1. Boyer, K.K. and Hult, G.T. (2005), “Extending the supply chain: integrating operations and marketing in the online grocery industry”, Journal of Operations Management, Vol. 23 No. 6, pp.642-661. https://doi.org/10.1016/j.jom.2005.01.003

  1. Boyer, K.K. and Hult, G.T. (2006), “Customer behavioral intentions for online purchases: An examination of fulfillment method and customer experience level”, Journal of Operations Management, Vol. 24 No. 2, pp.124-147. https://doi.org/10.1016/j.jom.2005.04.002

Journal of Retailing
  1. Lewis, M. (2006), “The effect of shipping fees on customer acquisition, customer retention, and purchase quantities”, Journal of Retailing, Vol. 82 No. 1, pp.13-23. https://doi.org/10.1016/j.jretai.2005.11.005

Journal of Retailing and Consumer Services
  1. Pelet, J.E., Durrieu, F. and Lick, E. (2020), “Label design of wines sold online: Effects of perceived authenticity on purchase intentions”, Journal of Retailing and Consumer Services, Vol. 55 (June) No. 102087, pp.1-12. https://doi.org/10.1016/j.jretconser.2020.102087

  1. Wilson-Jeanselme, M. and Reynolds, J. (2005), “Growth without profit: Explaining the Internet transaction profitability paradox”, Journal of Retailing and Consumer Services, Vol. 12 No. 3, pp.165-177. https://doi.org/10.1016/j.jretconser.2004.06.001

Journal of Small Business and Enterprise Development
  1. Jahanshahi, A.A., Zhang, S.X. and Brem, A. (2013), “E-commerce for SMEs: empirical insights from three countries”, Journal of Small Business and Enterprise Development, Vol. 20 No. 4, pp.849-865. https://doi.org/10.1108/JSBED-03-2012-0039

Journal of Service Research
  1. Heim, G.R. and Sinha, K.K. (2005), “Service product configurations in electronic business-to-consumer operations: A taxonomic analysis of electronic food retailers”, Journal of Service Research, Vol. 7 No. 4, pp.360-376. https://doi.org/10.1177/1094670504273969

  1. Quader, M.S. and Quader, M.R. (2008), “The utilization of e-commerce by traditional supermarkets in the UK through strategic alliances with Internet based companies”, Journal of Services Research, Vol. 8 No. 1, pp.177-211

MIT Sloan Management Review
  1. Westerman, G., Bonnet, D. and McAfee, A. (2014), “The nine elements of digital transformation”, MIT Sloan Management Review, Vol. 55 No. 3, pp.1-6

Research in Transportation Business and Management
  1. Rudolph, C. and Gruber, J. (2017), “Cargo cycles in commercial transport: Potentials, constraints, and recommendations”, Research in Transportation Business and Management, Vol. 24 September, pp.26-36. https://doi.org/10.1016/j.rtbm.2017.06.003

Resources, Conservation & Recycling
  1. Heard, B. R., Bandekar, M., Vassa, B. and Miller, S. A. (2019), “Comparison of life cycle environmental impacts from meal kits and grocery store meals”, Resources Conservation and Recycling, Vol.147, pp.189-200. Https://doi.org/10.1016/j.resconrec.2019.04.008

  1. Liu, G., Hu, J., Yang, Y., Xia, S. and Lim, M. K. (2020), “Vehicle routing problem in cold chain logistics: A joint distribution model with carbon trading mechanisms”, Resources, Conservation and Recycling, Vol. 156 May, pp.1-13. https://doi.org/10.1016/j.resconrec.2020.104715

Sustainability
  1. Aljohani, K. and Thompson, R.G. (2019), “A stakeholder-based evaluation of the most suitable and sustainable delivery fleet for freight consolidation policies in the inner-city area”, Sustainability, Vol. 11 No. 1, pp.124. https://doi.org/10.3390/su11010124

Technological Forecasting and Social Change
  1. Sung, T.K. (2006), “E-commerce critical success factors: East vs. West”, Technological Forecasting and Social Change, Vol. 73 No. 9, pp.1161-1177. https://doi.org/10.1016/j.techfore.2004.09.002

Thunderbird International Business Review
  1. Dubosson-Torbay, M., Osterwalder, A. and Pigneur, Y. (2002), “E-business model design, classification, and measurements”, Thunderbird International Business Review, Vol. 44 No. 1, pp.5-23. https://doi.org/10.1002/tie.1036

Transportation Research Part D: Transport and Environment
  1. Wygonik, E. and Goodchild, A.V. (2018), “Urban form and last-mile goods movement: Factors affecting vehicle miles travelled and emissions”, Transportation Research Part D: Transport and Environment, Vol. 61 June, pp.217-229. https://doi.org/10.1016/j.trd.2016.09.015

Transportation Science
  1. Campbell, A. M. and Savelsbergh, M. (2006), “Incentive schemes for attended home delivery services”, Transportation Science, Vol. 40 No. 3, pp.327-341. https://doi.org/10.1287/trsc.1050.0136

Trends in Food Science and Technology
  1. Chen, M.C., Hsu, C.L., Hsu, C.M. and Lee, Y.Y. (2014), “Ensuring the quality of e-shopping specialty foods through efficient logistics service”, Trends in Food Science and Technology, Vol. 35 No. 1, pp.69-82. https://doi.org/10.1016/j.tifs.2013.10.011

Other types of publications
  1. Prud'homme, A.M. and Boyer, K.K. (2005), “A comparison of in-store vs. online grocery customers”, in Kornum, N. and Bjerre, 8M. (Ed.s.), Grocery E-Commerce: Consumer Behaviour and Business Strategies, Edward Elgar Publishing, Portland, pp. 79-96

Appendix

Table A1.

References

Abushaikha, I., Salhieh, L. and Towers, N. (2018), “Improving distribution and business performance through lean warehousing”, International Journal of Retail and Distribution Management, Vol. 46 No. 8, pp. 780-800, doi: 10.1108/IJRDM-03-2018-0059.

Baporikar, N. (2020), “Logistics effectiveness through systems thinking”, International Journal of System Dynamics Applications, Vol. 9 No. 2, pp. 64-79, doi: 10.4018/IJSDA.2020040104.

Bèzes, C. (2021), “At the source of integrated interactions across channels”, International Journal of Retail and Distribution Management, Vol. 49 No. 7, pp. 899-918, doi: 10.1108/IJRDM-02-2021-0071.

Belavina, E., Girotra, K. and Kabra, A. (2017), “Online grocery retail: revenue models and environmental impact”, Management Science, Vol. 63 No. 6, pp. 1781-1799, doi: 10.1287/mnsc.2016.2430.

Bourlakis, M., Papagiannidis, S. and Fox, H. (2008), “E-consumer behaviour: past, present and future trajectories of an evolving retail revolution”, International Journal of E-Business Research, Vol. 4 No. 3, pp. 64-76, doi: 10.4018/jebr.2008070104.

Bouzaabia, R., Bouzaabia, O. and Capatina, A. (2013), “Retail logistics service quality: a cross-cultural survey on customer perceptions”, International Journal of Retail and Distribution Management, Vol. 41 No. 8, pp. 627-647, doi: 10.1108/IJRDM-02-2012-0012.

Boyer, K.K. and Hult, G.T. (2005), “Extending the supply chain: integrating operations and marketing in the online grocery industry”, Journal of Operations Management, Vol. 23 No. 6, pp. 642-661, doi: 10.1016/j.jom.2005.01.003.

Boyer, K.K., Prud’ homme, A.M. and Chung, W. (2009), “The last mile challenge: evaluating the effects of customer density and delivery window patterns”, Journal of Business Logistics, Vol. 30 No. 1, pp. 185-201, doi: 10.1002/j.2158-1592.2009.tb00104.x.

Bressolles, G. and Lang, G. (2019), “KPIs for performance measurement of e-fulfillment systems in multi-channel retailing: an exploratory study”, International Journal of Retail and Distribution Management, Vol. 48 No. 1, pp. 35-52, doi: 10.1108/IJRDM-10-2017-0259.

Castillo, V.E., Bell, J.E., Mollenkopf, D.A. and Stank, T.P. (2022), “Hybrid last mile delivery fleets with crowdsourcing: a systems view of managing the cost-service trade-off”, Journal of Business Logistics, Vol. 43, pp. 36-61, doi: 10.1111/jbl.12288.

Chhetri, P., Kam, B., Hung Lau, K., Corbitt, B. and Cheong, F. (2017), “Improving service responsiveness and delivery efficiency of retail networks”, International Journal of Retail and Distribution Management, Vol. 45 No. 3, pp. 271-291, doi: 10.1108/IJRDM-07-2016-0117.

Chow, G., Heaver, T.D. and Henriksson, L.E. (1994), “Logistics performance: definitions and measurements”, International Journal of Physical Distribution and Logistics Management, Vol. 24 No. 1, pp. 17-28, doi: 10.1108/09600039410055981.

Churchman, C.W. (1968), The Systems Approach, Dell Publishing Co., New York, NY.

Cotarelo, M., Calderón, H. and Fayos, T. (2021), “A further approach in omnichannel LSQ, satisfaction and customer loyalty”, International Journal of Retail and Distribution Management, Vol. 49 No. 8, pp. 1133-1153, doi: 10.1108/IJRDM-01-2020-0013.

Crainic, T.G., Perboli, G. and Rosano, M. (2018), “Simulation of intermodal freight transportation systems: a taxonomy”, European Journal of Operational Research, Vol. 270 No. 2, pp. 401-418, doi: 10.1016/j.ejor.2017.11.061.

de Borba, J.L.G., Magalhães, M.R.d., Filgueiras, R.S. and Bouzon, M. (2020), “Barriers in omnichannel retailing returns: a conceptual framework”, International Journal of Retail and Distribution Management, Vol. 49 No. 1, pp. 121-143, doi: 10.1108/IJRDM-04-2020-0140.

Delafenestre, R. (2019), “New business models in supply chains: a bibliometric study”, International Journal of Retail and Distribution Management, Vol. 47 No. 12, pp. 1283-1299, doi: 10.1108/IJRDM-12-2018-0281.

Elgazzar, S., Tipi, N. and Jones, G. (2019), “Key characteristics for designing a supply chain performance measurement system”, International Journal of Productivity and Performance Management, Vol. 68 No. 2, pp. 296-318, doi: 10.1108/IJPPM-04-2018-0147.

Fernie, J., Sparks, L. and McKinnon, A.C. (2010), “Retail logistics in the UK: past, present and future”, International Journal of Retail and Distribution Management, Vol. 38 Nos 11/12, pp. 894-914, doi: 10.1108/09590551011085975.

Fugate, B.S., Mentzer, J.T. and Stank, T.P. (2010), “Logistics performance: efficiency, effectiveness, and differentiation”, Journal of Business Logistics, Vol. 31 No. 1, pp. 43-62, doi: 10.1002/j.2158-1592.2010.tb00127.x.

Hagberg, J. and Holmberg, U. (2017), “Travel modes in grocery shopping”, International Journal of Retail and Distribution Management, Vol. 45 No. 9, pp. 991-1010, doi: 10.1108/IJRDM-08-2016-0134.

Halevi, G., Moed, H. and Bar-Ilan, J. (2017), “Suitability of Google Scholar as a source of scientific information and as a source of data for scientific evaluation—review of the literature”, Journal of Informetrics, Vol. 11 No. 3, pp. 823-834, doi: 10.1016/j.joi.2017.06.005.

He, Z. (2020), “The challenges in sustainability of urban freight network design and distribution innovations: a systematic literature review”, International Journal of Physical Distribution and Logistics Management, Vol. 50 No. 6, pp. 601-640, doi: 10.1108/IJPDLM-05-2019-0154.

Hübner, A., Holzapfel, A. and Kuhn, H. (2016), “Distribution systems in omni-channel retailing”, Business Research, Vol. 9 No. 2, pp. 255-296, doi: 10.1007/s40685-016-0034-7.

Jain, N.K., Gajjar, H., Shah, B.J. and Sadh, A. (2017), “E-fulfillment dimensions and its influence on customers in e-tailing: a critical review”, Asia Pacific Journal of Marketing and Logistics, Vol. 29 No. 2, pp. 347-369, doi: 10.1108/APJML-11-2015-0167.

Jocevski, M., Arvidsson, N., Miragliotta, G., Ghezzi, A. and Mangiaracina, R. (2019), “Transitions towards omni-channel retailing strategies: a business model perspective”, International Journal of Retail and Distribution Management, Vol. 47 No. 2, pp. 78-93, doi: 10.1108/IJRDM-08-2018-0176.

Kannan, P.K. and Li, H. (2017), “Digital marketing: a framework, review and research agenda”, International Journal of Research in Marketing, Vol. 34 No. 1, pp. 22-45, doi: 10.1016/j.ijresmar.2016.11.006.

Kembro, J. and Norrman, A. (2019), “Exploring trends, implications and challenges for logistics information systems in omni-channels: Swedish retailers' perception”, International Journal of Retail and Distribution Management, Vol. 47 No. 4, pp. 384-411, doi: 10.1108/IJRDM-07-2017-0141.

Kuhn, H. and Sternbeck, M.G. (2013), “Integrative retail logistics: an exploratory study”, Operations Management Research, Vol. 6 Nos 1/2, pp. 2-18, doi: 10.1007/s12063-012-0075-9.

Kumar, A. and Anjaly, B. (2017), “How to measure post-purchase customer experience in online retailing? A scale development study”, International Journal of Retail and Distribution Management, Vol. 45 No. 12, pp. 1277-1297, doi: 10.1108/IJRDM-01-2017-0002.

Kumar, V., Chibuzo, E.N., Garza-Reyes, J.A., Kumari, A., Rocha-Lona, L. and Lopez-Torres, G.C. (2017), “The impact of supply chain integration on performance: evidence from the UK food sector”, in Pellicciari, M. and Peruzzini, M. (Eds) 27th International Conference on Flexible Automation and Intelligent Manufacturing, Modena, Italy, via Procedia Manufacturing, Vol. 11, pp.814-821, doi: 10.1016/j.promfg.2017.07.183.

Lim, S.F.W., Jin, X. and Srai, J.S. (2018), “Consumer-driven e-commerce: a literature review, design framework, and research agenda on last-mile logistics models”, International Journal of Physical Distribution and Logistics Management, Vol. 48 No. 3, pp. 308-332, doi: 10.1108/IJPDLM-02-2017-0081.

Mackelprang, A.W., Robinson, J.L., Bernardes, E. and Webb, G.S. (2014), “The relationship between strategic supply chain integration and performance: a meta-analytic evaluation and implications for supply chain management research”, Journal of Business Logistics, Vol. 35 No. 1, pp. 71-96, doi: 10.1111/jbl.12023.

Mangiaracina, R., Marchet, G., Perotti, S. and Tumino, A. (2015), “A review of the environmental implications of B2C e-commerce: a logistics perspective”, International Journal of Physical Distribution and Logistics Management, Vol. 45 No. 6, pp. 565-591, doi: 10.1108/IJPDLM-06-2014-0133.

Melkonyan, A., Gruchmann, T., Lohmar, F., Kamath, V. and Spinler, S. (2020), “Sustainability assessment of last-mile logistics and distribution strategies: the case of local food networks”, International Journal of Production Economics, Vol. 228 107746/October, pp. 1-17, doi: 10.1016/j.ijpe.2020.107746.

Milioti, C., Pramatari, K. and Zampou, E. (2020), “Choice of prevailing delivery methods in e-grocery: a stated preference ranking experiment”, International Journal of Retail and Distribution Management, Vol. 49 No. 2, pp. 281-298, doi: 10.1108/IJRDM-08-2019-0260.

Mingers, J. and White, L. (2010), “A review of the recent contribution of systems thinking to operational research and management science”, European Journal of Operational Research, Vol. 207 No. 3, pp. 1147-1161, doi: 10.1016/j.ejor.2009.12.019.

Morris, H., Harvey, C. and Kelly, A. (2009), “Journal rankings and the ABS Journal Quality Guide”, Management Decision, Vol. 47 No. 9, pp. 1441-1451, doi: 10.1108/00251740910995648.

Öberg, C., Huge-Brodin, M. and Björklund, M. (2012), “Applying a network level in environmental impact assessment”, Journal of Business Research, Vol. 65 No. 2, pp. 247-255, doi: 10.1016/j.jbusres.2011.05.026.

Oeser, G., Aygün, T., Balan, C.-L., Corsten, T., Dechêne, C., Ibald, R., Paffrath, R. and Schuckel, M.T. (2018), “Implications of the ageing population for the food demand chain in Germany”, International Journal of Retail and Distribution Management, Vol. 46 No. 2, pp. 163-193, doi: 10.1108/IJRDM-01-2017-0012.

Olsson, J., Hellström, D. and Pålsson, H. (2019), “Framework of last mile logistics research: a systematic review of the literature”, Sustainability, Vol. 11 No. 24, p. 7131, doi: 10.3390/su11247131.

Paidi, V., Nyberg, R. and Håkansson, J. (2020), “Dynamic scheduling and communication system to manage last mile handovers”, Logistics, Vol. 4 No. 2, p. 13, MDPI AG doi: 10.3390/logistics4020013.

Salhieh, L., Shehadeh, M., Abushaikha, I. and Towers, N. (2021), “Integrating vehicle tracking and routing systems in retail distribution management”, International Journal of Retail and Distribution Management, Vol. 49 No. 8, pp. 1154-1177, doi: 10.1108/IJRDM-12-2019-0400.

Sallnäs, U. and Björklund, M. (2020), “Consumers' influence on the greening of distribution – exploring the communication between logistics service providers, e-tailers and consumers”, International Journal of Retail and Distribution Management, Vol. 48 No. 11, pp. 1177-1193, doi: 10.1108/IJRDM-07-2019-0213.

Seghezzi, A. and Mangiaracina, R. (2020), “On-demand food delivery: investigating the economic performances”, International Journal of Retail and Distribution Management, Vol. 49 No. 4, pp. 531-549, doi: 10.1108/IJRDM-02-2020-0043.

Shah, B. and Khanzode, V. (2017), “Storage allocation framework for designing lean buffers in forward-reserve model: a test case”, International Journal of Retail and Distribution Management, Vol. 45 No. 1, pp. 90-118, doi: 10.1108/IJRDM-07-2016-0112.

Sorkun, M.F., Yumurtacı Hüseyinoğlu, I.Ö. and Börühan, G. (2020), “Omni-channel capability and customer satisfaction: mediating roles of flexibility and operational logistics service quality”, International Journal of Retail and Distribution Management, Vol. 48 No. 6, pp. 629-648, doi: 10.1108/IJRDM-07-2019-0235.

Tranfield, D.R., Denyer, D. and Smart, P. (2003), “Towards a methodology for developing evidence-informed management knowledge by means of systematic review”, British Journal of Management, Vol. 14 No. 3, pp. 207-222, doi: 10.1111/1467-8551.00375.

Wiese, A., Kellner, J., Lietke, B., Toporowski, W. and Zielke, S. (2012), “Sustainability in retailing – a summative content analysis”, International Journal of Retail and Distribution Management, Vol. 40 No. 4, pp. 318-335, doi: 10.1108/09590551211211792.

Xiao, Z., Wang, J.J. and Liu, Q. (2018), “The impacts of final delivery solutions on e-shopping usage behaviour: the case of Shenzhen, China”, International Journal of Retail and Distribution Management, Vol. 46 No. 1, pp. 2-20, doi: 10.1108/IJRDM-03-2016-0036.

Xing, Y. and Grant, D.B. (2006), “Developing a framework for measuring physical distribution service quality of multi-channel and ‘pure player’ internet retailers”, International Journal of Retail and Distribution Management, Vol. 34 Nos 4/5, pp. 278-289, doi: 10.1108/09590550610660233.

Zhang, J., Onal, S., Das, R., Helminsky, A. and Das, S. (2019), “Fulfilment time performance of online retailers – an empirical analysis”, International Journal of Retail and Distribution Management, Vol. 47 No. 5, pp. 493-510, doi: 10.1108/IJRDM-10-2017-0237.

Zondag, M.M., Mueller, E.F. and Ferrin, B.G. (2017), “The application of value nets in food supply chains: a multiple case study”, Scandinavian Journal of Management, Vol. 33 No. 4, pp. 199-212, doi: 10.1016/j.scaman.2017.10.002.

Acknowledgements

The authors would like to acknowledge the funding from The Kamprad Family Foundation for Entrepreneurship, Research & Charity (Grant no. 20180076) for this research. The funding organisation did not influence the research process of the study. The authors are also grateful to the Editor and Reviewers for their comments on the manuscript throughout the revision process.

Corresponding author

Madelen Lagin is the corresponding author and can be contacted at: mli@du.se

About the authors

Madelen Lagin is a senior lecturer in Business Administration at Dalarna University. Her research interest focus on cooperative strategies and decision-making, including last-mile logistics, actors' roles, impact and relations, with publications in the following journals: Journal of Retailing & Distribution Management, and International Review of Retail, Distribution and Consumer Research.

Johan Håkansson is a full professor in Microdata Analysis at Dalarna University. His research interests focus on transportation and include last mile logistics, decision support systems, transport efficiency and urban mobility, with publications in numerous journals including Transport Research, European Journal of Operations Research, Journal of Regional Science and Journal of Retailing & Distribution Management.

Carin Nordström is a senior lecturer in Entrepreneurship and Innovation at Dalarna University. Her research interests include hybrid entrepreneurship, social entrepreneurship, passion, business models, locally produced food and logistics, with publications in journals such as Baltic Journal of Management and Business Venturing Insights.

Roger G. Nyberg is a senior lecturer in Informatics/Computer Science at Dalarna University. His professional skills and research focus include data science, pattern recognition, computational intelligence, monitoring, planning, research methodology, applied statistics, machine learning and machine vision. His work is often about how to automate or semi-automate human decision-making. In this context, focus is on why humans take certain decisions and how to make actions more rational. He has published his work in journals such as Logistics, International Journal of Risk Assessment and Management, IET Intelligent Transport Systems and Journal of Intelligent Systems.

Christina Öberg is a full professor in Business Administration at Karlstad University and associated with the Ratio Institute and Leeds University. Her research interests concern mergers and acquisitions, customer relationships, innovations, sustainability and new ways to pursue business, including the sharing economy and effects of additive manufacturing. She has previously published in such journals as Journal of Business Research, Industrial Marketing Management, International Marketing Review, European Journal of Marketing, Information, Technology & People, Entrepreneurship & Regional Development, Supply Chain Management: An International Journal and Production Planning & Control.

Related articles