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This study examines the different effects of service recovery strategies on customers' future intentions when online shoppers were experiencing delivery failures. Two types of problem severity are evaluated: wrong-product delivery (issues with the product quality or quantity) and late delivery. This study also investigates the impact of service criticality on the relationship between service recovery strategies and customers' future intentions.

This study employs experimental research with 123 online shoppers as participants. Following the results, a subsequent test is conducted to examine the effect of participants' demographics on future intentions. Finally, the current study elaborates the findings using qualitative research, interviewing both sides impacted by the service failures: online shoppers and e-retail managers.

The findings show that complementing product replacement with monetary compensation is the most effective strategy to improve repurchase intention after a dissatisfaction moment. This effect is indifferent to service criticality and severity. Age influences the participants' repurchase intentions, in which younger people are less tolerant of service failures. In contrast, gender and education level do not provide any differences. To prevent delivery failures, managers participating in this study suggest several best practices regarding systems and infrastructure, people and coordination and collaboration with logistics partners.

The study mainly examines a limited type of service and service failures. Further studies are encouraged to expand the variables and scenarios, as well as to employ more distinctive methods, to enrich the findings related to recovery strategy in the e-commerce industry.

Given proper compensation, service failure could create momentum for online retailers to boost customer loyalty. This study suggests that managers design the most effective service recovery to win customers back to the business.

This paper enriches the literature related to a service recovery strategy, particularly within the online shopping context.

Stock keeping unit (SKU) classifications are widely used in the field of production and operations management. Although many theoretical and practical examples of classifications exist, there are no overviews of the current literature, and general guidelines are lacking with respect to method selection for classifying SKUs. The purpose of this paper is to systematically synthesise the earlier work in this area, and to conceptualise and discuss the factors that influence the choice of a specific SKU classification.

The paper structurally reviews existing contributions and synthesises these into a conceptual framework for SKU classification.

How SKUs are classified depends on the classification aim, the context and the method that is chosen. In total, three main production and operations management aims were found: inventory management, forecasting and production strategy. Within the method three decisions are identified to come to a classification: the characteristics, the classification technique and the operationalisation of the classes.

Drawing on the literature survey, the authors conclude with a conceptual framework describing the factors that influence SKU classification. Further research could use this framework to develop guidelines for real‐life applications.

Examples from a variety of industries and general directions are provided which managers could use to develop their own SKU classification.

The paper aims to advance the literature on SKU classification from the level of individual examples to a conceptual level and provides directions on how to develop a SKU classification.

Failure mode and effect analysis (FMEA) is an analysis technique for identifying and eliminating known and/or potential failures and problems from products, processes or systems. Notwithstanding its diffusion, traditional FMEA has several limitations. Lately, scientific research has been focused on improving said limitations, yet the process is still ongoing. The purpose of this paper is to support developments in this area.

The paper improves the conventional FMEA by using the method of pairwise comparison to establish the relative importance of the input factors in risk priority number calculation, and Markov chains to calculate risk distributions in the long term.

The functioning and usefulness of the proposed methodology is demonstrated through an application to the construction industry, one of the world’s biggest industrial sectors, dogged by a high rate of work-related injuries and casualties.

Having demonstrated the applicability of the novel methodology to a real domain, the paper contributes to the process of overcoming traditional FMEA limitations.

The purpose of this research is to investigate the contingent adoption of Additive Manufacturing (AM) and propose a typology to evaluate its adoption viability within a firm's supply chain.

By conducting semi-structured interviews of practitioners with deep knowledge of AM and supply chains from diverse industries, this research explores the contingent factors influencing AM adoption and their interaction.

While the AM literature is growing, there is a lack of research investigating how contingent factors influence AM adoption. By reviewing the extant literature on the benefits and barriers of AM, we explain the underlying contingencies that enact them. Further, we use an exploratory approach to validate and uncover underexplored contingent factors that influence AM adoption and group them into technological, organizational and strategic factors. By anchoring to a selected set of contingent factors, a typological framework is developed to explain when and how AM is a viable option.

This study focuses on specific industries such as automotive, machine manufacturing, aerospace and defense. Scholars are encouraged to explore the contextual factors affecting AM adoption in particular industries to expand our findings. The authors also acknowledge that the robustness of their framework can be enhanced by integrating the remaining contingent factors.

The developed typological framework provides a pathway for practitioners to see how and when AM can be useful in their supply chains.

This is the first paper in the supply chain management literature to synthesize contingent factors and identify some overlooked factors for AM adoption. The research is also unique in explaining the interaction among selected factors to provide a typological framework for AM adoption. This research provides novel insights for managers to understand when and where to adopt AM and the key contingent factors involved in AM adoption.

The purpose of this paper is to contribute to the understanding of the relationship between information sharing and performance of perishable product supply chains (PPSC). Building on transaction cost economics (TCE), organisational information processing theory (OIPT), and contingency theory (CT), this study proposes a theoretical framework to guide future research into information sharing in perishable product supply chains (IS-PPSC).

Using the systematic literature review methodology, 48 peer-reviewed articles are carefully selected, mapped, and assessed. Template analysis is performed to unravel the relationship mechanisms between information sharing and PPSC performance.

The authors find that the relationship between information sharing and PPSC performance is currently unclear, and there is inconsistency in the positioning of information sharing among constructs and variables in the IS-PPSC literature. This implies a requirement to refine the relationship between information sharing and PPSC performance. The review also revealed that the role of perishable product characteristics has largely been ignored in existing research.

This study applies relevant multiple theoretical perspectives to overcome the ambiguity of the IS-PPSC literature and contributes nine propositions to guide future research. Accordingly, this study contributes to the refined roles of relationship uncertainty, environmental uncertainty, information sharing capabilities, and perishable product characteristics in shaping the relationship between information sharing and PPSC performance.

The purpose of this paper is to identify, quantify and establish relationship (i.e. cause and effect) among various supplier development program enablers (SDPEs) in a specific manufacturing environment.

The proposed methodology runs into four phases, i.e. defining supplier development program (SDP) environment, identifying relevant SDPEs, collecting experts’ qualitative opinions regarding SDPEs and analyzing the SDPEs using Fuzzy DEMATEL (Decision Making Trial and Evaluation Laboratory). The fourth phase is programmed using Matlab 7.10.0 (R2010a). The proposed methodology is implemented in an Indian manufacturing company and the results are analyzed to provide directions for the company while implementing SDPs.

The proposed methodology leads to the ranking of SDPEs, classification of SDPEs into cause and effect groups and establishment of interactions for each SDPE using impact relationship map. Of the 20 SDPEs considered in the analysis, “top management commitment” and “mutual visits by competent personnel from both sides” are the two most important SDPEs for implementing SDP in an Indian manufacturing company taken as a case study. The outcomes are verified by consulting the said company’s experts and their validity is confirmed.

Because the results obtained are specific to a manufacturing environment, they cannot be generalized. However, the proposed approach can be adopted for analyzing SDPEs in any manufacturing environment, provided the set of SDPEs is selected considering its priorities.

The proposed methodology will identify the SDPEs to be managed for successful implementation of SDPs.

The proposed methodology has the capability to rank the SDPEs and their interrelationships. This will definitely help supply chain managers to precisely choose and manipulate the SDPEs for successful implementation of SDP.

Engineering service (ES) development, particularly with supplier co-creation, is nontrivial, and the literature has acknowledged the high relevance of uncertainty in this context. This study aims to investigate the relationship between different supplier co-creation modes (operationally independent [OI] and operationally dependent [OD]) and uncertainty criticality arising during ES development.

This study develops a conceptual framework of five uncertainty types by synthesizing the relevant literature from service management and new product development. This framework guided the empirical work of two in-depth case studies, describing uncertainty criticality in OI and OD supplier co-creation.

The findings show that environmental and organizational uncertainty were generally of high criticality for ES development independently of the supplier co-creation mode. Moreover, uncertainty criticality varied between the two cases, with higher criticality of technical and relational uncertainty as well as less resource uncertainty experienced by the focal organization in the OD case. This suggests that supplier co-creation constitutes an uncertainty reallocation.

Further research is needed to test the generalizability of the qualitative results through quantitative studies.

This research contributes to the service management literature by showing the varying uncertainty profiles manufacturing organizations face when engaging in different supplier co-creation modes. Furthermore, this research provides novel insights on ES development to the broader discussion on ES management.

This work aims at integrating materials management with project management in the context of manufacturing of complex products which require a variety of items. To achieve this, we propose two prioritization measures of items: material criticality (MC) at activity level and overall criticality (OC) at project level by incorporating project network characteristic through activity criticality (AC) values.

The costs or penalties which determine criticality of items are hidden in nature and are difficult to measure and model mathematically. Hence, Fuzzy Inference System (FIS), which captures experts’ tacit knowledge in the form of linguistic If‐Then rules has been used.

OC obtained can be used as a measure to prioritize items for procurement aligned with on‐site build strategy and as a surrogate measure of shortage cost coefficient for inventory models. The analyses of output to observe the effect of AC on OC values of items, clearly demonstrate the novelty and importance of incorporating project network characteristics in materials management decision making.

In this work, we are able to leverage managerial tacit knowledge derived through years of experience and convert it into a readily usable quantitative parameter OC for prioritization of items to be procured. For identifying the input parameters for OC, we brought in the new perspective of including project network characteristics to align materials and project management.

The purpose of this paper is to present a new index of social vulnerability (SV), based on local level data [statistical blocks (SBs)]. This same methodology was applied before at the municipal level, which is a level of analysis that under-evaluates local spots of high SV, by one side, and generalizes the coverage of support capacity equipment and infrastructure. The geographical level of detail of the input data allows to overcome those limitations and better inform infra-municipal risk practitioners and planners.

The assessment of SV in this paper adopts an inductive approach. The research context of this conceptual and methodological proposal derived from the need to operationalize the concept of SV as a planning tool. This approach required to distinguish between the components of criticality and support capability, as their assessment provides knowledge with distinct applications in risk management. The statistical procedure is based on principal components analysis, using the SB as the unit of analysis.

Support capability acts as a counter-weight of criticality. This understanding is well illustrated in the mapping of each component and the final score of SV. The methodological approach allowed to identify the drivers of criticality and support capability in each SB, aiding decision-makers and risk practitioners in finding the vulnerability forcers that require more attention (public or private social equipment, housing policies, emergency anticipatory measures, etc.).

An original approach to SV assessments is the consideration of the components of criticality and support capability. The results allow for the definition of adapted and specific strategies of risk mitigation and civil protection measures to distinct types of risk groups and by different stakeholders and risk practitioners. By predicting the impact and the recovery capacity of communities, the results have applicability in several fields of risk governance as, for example, risk communication and involvement, social intervention (health, education and housing), emergency response, contingency planning, early warning and spatial planning.

Operating as a commodity disables the scope of differentiation. In turn, the organization becomes vulnerable to competition. A strong brand ensures the selling company to get premium prices and in the best case rejection of competitive products by the buyers. Branding was often seen as the province of business‐to‐consumer (B2C) products. But in reality, the role of brand in business‐to‐business (B2B) market is also important. B2B sector is fiercely competitive in nature and in the recent past a strong need has been felt by small to medium‐sized enterprises (SMEs) operating in this sector to elevate from commodity construct to brand for sustainable competitive advantages. Products from SMEs, in the B2B market, have nearly identical physical looks and performance specifications. As a result, it is difficult to achieve differentiation. In this backdrop, the purpose of this paper is to study branding readiness of SMEs which are operating in a B2B market and a strategic road map has been proposed.

An empirical analysis has been made to understand relevance, objectives, benefits and hindrances of branding in this industry. In the second stage, a verbal conceptual model has been proposed to explain strategic steps of branding for SMEs which are operating in the B2B sector.

From the research it has been found that SMEs having different motivations behind branding based on criticality of the components and their market orientation. A strategic branding roadmap has been proposed in this section. Construction of the “Brand Initiative Framework” involves plotting of a “degree of product criticality” and “degree of market orientation” in the matrix form, each made of two states – high and low. The objective of this decision matrix is to guide SMEs operating in B2B sector to opt for requisite branding initiatives.

The proposed “Brand Initiatives Framework” can be of immense use to SMEs for managing branding initiatives to ensure clutter free differentiation with target segment.

This paper presents a generic approach that may work beyond country boundaries. The conceptual model of “Brand Initiative Framework” is of immense help to manage branding activities in a strategically profitable way.