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Manufacturers face various challenges and risks during their digital servitization (DS), due to the complexity caused by introducing breakthrough technologies, increasingly complex product-service solutions and new stakeholders in the business network. The process necessitates the implementation of various changes that usually happen over a long period of time. Using complexity management as a theoretical lens, this paper delves into manufacturers’ DS journeys and explores how manufacturers manage the associated complexities.

This paper investigates the DS journey of two manufacturers in a longitudinal case study from 2014 to 2021.

Three main complexity management actions during the DS journey were identified: shaping the digital service system, shaping the organization and shaping the network. Tied to different types of complexities, these actions demonstrate how manufacturers navigate their journey. The findings also reveal different complexity management approaches used at the different stages of this journey.

This paper offers a comprehensive framework for understanding complexity management in the DS journey, including the types of complexities, complexity management actions and complexity management approaches and their rationale. This paper shows that different requirements are created during emerge, consolidate and evolve stages of the DS journey. Manufacturers need a dynamic approach that considers changes in complexities and actions over time.

This study aimed to the attributes, consequences and personal values that motivate the behavior of consumers of fruits and vegetables (FV) at local markets and how these elements are associated with food safety.

This is a qualitative research that used the laddering in-depth interview technique for data collection. Fifty interviews were conducted with consumers from Minas Gerais, Brazil. From the codification of the interview content, a hierarchical value map was constructed, showing the relationships between the attributes, consequences and values involved in the consumers’ purchasing decision.

Consumers value characteristics related to the origin of the product and the way it is produced and marketed. They seek particular benefits – such as satisfaction with the purchase, care for their health/well-being and safety when consuming food – and social benefits, such as the possibility of contributing to the local economy. Issues related to hygiene, organization, exposure and handling of products were some of the concerns reported by respondents with regard to food safety.

It is worth highlighting the application of the laddering technique itself. Analyzing the predictive validity of the method, there is a propensity for biases linked to possible interference by the researcher, especially in the coding stage of the elements.

This study can be used by producers, marketing professionals and public policymakers to promote FV sold at local markets and to encourage the improvement of food safety practices.

The research points to five consumer segments according to the different motivations that guide their purchase behavior for local FV. In addition, a focus is given to food safety, revealing its importance in the investigated context.

Purpose: This research investigates how producers of fast-moving consumer goods (FMCG) in Karachi, Pakistan, embrace sustainable manufacturing and consumption practices.

Study design/methodology/approach: This study employed a mixed research design, incorporating both qualitative and quantitative approaches. The primary method of data collecting utilised in this study was semi-structured interviews. The survey sampled 11 FMCG manufacturers, and the data were analysed using thematic analysis.

Findings: The research revealed that economic variables were crucial in adopting sustainable consumption and production (SCP) practices among Karachi’s FMCG businesses. The economic reasons were motivated by the notion that adopting sustainable practices could result in financial benefits and enhanced market competitiveness. The research additionally discovered that consumer preferences were pivotal in stimulating sustainable practices within the FMCG business. Manufacturers indicated that adopting sustainable products and packaging was driven mainly by consumer demand.

Originality/value: This study contributes to the literature on SCP within the FMCG business. It offers valuable insights into the factors influencing sustainable practices and customer preferences. This study emphasises the importance of economic, social, and environmental aspects in fostering sustainable practices within the FMCG industry, specifically focusing on developing nation environments such as Karachi. This study’s findings can contribute valuable insights for policy formulation and decision-making processes about SCP within Karachi’s FMCG business and other similar contexts.

Identifying and prioritizing supply chain risk is significant from any product’s quality and reliability perspective. Under an input-process-output workflow, conventional risk prioritization uses a risk priority number (RPN) aligned to the risk analysis. Imprecise information coupled with a lack of dealing with hesitancy margins enlarges the scope, leading to improper assessment of risks. This significantly affects monitoring quality and performance. Against the backdrop, a methodology that identifies and prioritizes the operational supply chain risk factors signifies better risk assessment.

The study proposes a multi-criteria model for risk prioritization involving multiple decision-makers (DMs). The methodology offers a robust, hybrid system based on the Intuitionistic Fuzzy (IF) Set merged with the “Technique for Order Performance by Similarity to Ideal Solution.” The nature of the model is robust. The same is shown by applying fuzzy concepts under multi-criteria decision-making (MCDM) to prioritize the identified business risks for better assessment.

The proposed IF Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) for risk prioritization model can improve the decisions within organizations that make up the chains, thus guaranteeing a “better quality in risk management.” Establishing an efficient representation of uncertain information related to traditional failure mode and effects analysis (FMEA) treatment involving multiple DMs means identifying potential risks in advance and providing better supply chain control.

In a company’s supply chain, blockchain allows data storage and transparent transmission of flows with traceability, privacy, security and transparency (Roy et al., 2022). They asserted that blockchain technology has great potential for traceability. Since risk assessment in supply chain operations can be treated as a traceability problem, further research is needed to use blockchain technologies. Lastly, issues like risk will be better assessed if predicted well; further research demands the suitability of applying predictive analysis on risk.

The study proposes a hybrid framework based on the generic risk assessment and MCDM methodologies under a fuzzy environment system. By this, the authors try to address the supply chain risk assessment and mitigation framework better than the conventional one. To the best of their knowledge, no study is found in existing literature attempting to explore the efficacy of the proposed hybrid approach over the traditional RPN system in prime sectors like steel (with production planning data). The validation experiment indicates the effectiveness of the results obtained from the proposed IF TOPSIS Approach to Risk Prioritization methodology is more practical and resembles the actual scenario compared to those obtained using the traditional RPN system (Kim et al., 2018; Kumar et al., 2018).

This study provides mathematical models to simulate the supply chain risk assessment, thus helping the manufacturer rank the risk level. In the end, the authors apply this model in a big-sized organization to validate its accuracy. The authors validate the proposed approach to an integrated steel plant impacting the production planning process. The model’s outcome substantially adds value to the current risk assessment and prioritization, significantly affecting better risk management quality.

The study’s purpose is to investigate the constraints and facilitators influencing skiing participation in Beijing. This research includes three segments based on the frequency of skiing participation (i.e. non-, low-frequency-, and high-frequency skiers). By doing so, the study offers an enhanced understanding of the Chinese skiing market and unveils insights assisting industry professionals to effectively address their customers' diverse needs and expectations.

An online survey was developed based on prior research and consisted of four sections: (1) skiing participation; (2) constraints; (3) facilitators; (4) demographics. Items in the constraint and facilitator scale were measured using a 7-point Likert scale. A total of 409 participants completed the survey. The participants included 137 non-skiers, 134 low-frequency skiers, and 138 high-frequency skiers.

Through an exploratory factor analysis, three constructs emerged: general constraints, facilitators and learning constraints. As expected, facilitators were a positive predictor of skiing participation. Importantly, the emergent construct of learning constraints was a negative predictor of skiing and yet, the construct of general constraints was insignificant. Furthermore, the three segments differ significantly in household status, income, and education level.

These results support previous research noting the relevance in skiing participation of the dimensions: facilitators and learning constraints. The findings point to the need for ski resorts in Beijing to offer instructional sessions for beginners so they may become familiar with skiing fundamentals and enhance their confidence, particularly among nonskiers and low-frequency skiers.

This study aims to investigate the combined use of System Dynamics (SD) applications in Enterprise Engineering (EE) research and practice. SD application in EE is becoming widely accepted as a tool to support decision-making processes and for capturing relationships within enterprises.

A systematic literature review (SLR) is conducted using a standard SLR method to provide a comprehensive review of existing literature. The search was conducted on ten platforms identifying 30 publications which were analysed through the use and development of a codebook.

The SLR showed that 90% of the result set consisted of peer-reviewed academic conferences and journal papers. The SLR identified a highly dispersed author set of 83 authors. Amongst these authors, Vinay Kulkarni was an active author who has co-authored up to four publications in this research area. The analysis further revealed that the combined use of SD applications and EE is an emerging research area that still needs to develop in maturity. While all phases of EE have received attention, the current research work is more focused on the design phase. The important gap between model development and implementation is identified.

The study elucidates the existing status of interdisciplinary research combining techniques from the SD and EE disciplines, suggesting future research topics that combine the strengths of these existing disciplines.

While prior studies have explored the relationship between visual appeal and purchasing decisions, the role of bookmarking has largely been underemphasized. This research aims to address this gap by focusing on the impact of bookmarking on consumer behavior, guided by the cognitive load theory and dual-system theory.

The authors executed a controlled experiment and analyzed the results using a two-stage regression method that linked visual appeal, bookmarking and purchase intent. Further empirical analysis was conducted to authenticate the authors' proposed model, utilizing real-world mobile commerce data from a clothing company.

This study's findings suggest that visual appeal influences purchase intent primarily through the full mediation of bookmarking, rather than exerting a direct influence. Furthermore, an increase in colorfulness corresponds positively with visual appeal, while visual complexity exhibits an inverted U-shaped relationship with it.

This study provides novel insights into the choice-set formation process through the theoretical lens of dual-system theory. Additionally, the authors employed an image processing technique to quantify a product's visual appeal as depicted in a photograph. This study also incorporates a comprehensive econometric analysis to connect the objective aspects of visual appeal with subjective responses.

When is it more profitable for multinational manufacturers to manufacture in high-cost environments and when in low-cost environments? While the literature offers many cues to answer this question, too little empirical research directly addresses this. In this study, we quantitatively and empirically investigate the financial effect of companies' production footprint in low-cost and high-cost environments for different types of production networks.

Using the data of 770 multinational manufacturing companies, we analyze the relationship between production footprints and profitability during four calendar semesters in 2018 and 2019 (N = 2,940), investigating the moderating role of companies' production network type.

We find that companies with networks distinguished by both high levels of product complexity and process sophistication profit the most from producing to a greater extent in high-cost countries. For these companies, shifting production to low-cost countries would be associated with negative performance implications.

Our findings suggest that the production geography of companies should be attuned to their network type, as defined by the companies' process sophistication and product complexity. Manufacturing in low-cost countries is not always the best choice, as doing so can adversely affect profits if the products are highly innovative and the production processes are complex.

We contribute to the scarce empirical literature on managing global production networks and provide a data-driven analysis that contributes to answering some of the enduring questions in this critical area.

This paper aims to provide a comprehensive framework on how and when musical elements such as keys, complexity, tempo and volume influence consumers’ mood, attention, information recall, product evaluation and purchase decisions in the context of retail therapy.

This paper builds on a critical literature review to develop a conceptual framework and formulate relevant propositions, leveraging self-regulation and self-control theories.

Through our analysis of these studies, we found that in musical retail therapy, minor keys paired with high complexity can intensify negative moods and negative product evaluation. Conversely, major keys combined with low complexity can moderate negative and positive moods, leading to positive product evaluations. We argue that high tempo and high volume can invoke high arousal and low impulse control, leading to low attention and low recall. This subsequently moderates the negative mood, resulting in weak negative product evaluation. Low tempo and low volume, however, invoke low arousal and high impulse control, leading to high attention and high recall, which moderates negative mood and negative product evaluation.

Reflecting on the limitations of the existing studies, this conceptual work proposes a comprehensive theoretical framework for understanding the significance of musical elements in retail therapy that can enhance consumers moods and experiences. Further, the current paper is different from the existing literature in that it helps academic researchers and marketers understand different ways to use musical elements that can positively affect consumer behavior in a complex situation like retail therapy.

This study aims to evaluate the impact of product complexity, product involvement and product diagnosticity on shaping webrooming behavior in emerging fashion retailing, with product knowledge acting as a moderator and information processing, and uncertainty reduction theory contributing as the theoretical foundation.

In total, 371 responses were collected from fashionable consumers who had recently purchased fashion products via a purposive sampling approach, and the data were analyzed using structural equation modeling and PROCESS macro.

The results illustrated that product complexity had a significant impact on product involvement and product diagnosticity, and consumer attitude. Attitude, in turn, had a favorable impact on webrooming behavior. Likewise, product diagnosticity and product involvement had a positive mediating association between product complexity and consumer attitude. Product knowledge significantly moderated the relationship between product complexity, product involvement, and consumer attitude, but it exhibited a negative moderation association between product complexity, product diagnosticity, and attitude.

This study represents a novel research endeavor, shedding light on webrooming from the perspective of product attributes in fashion retailing. It contributes to the growing body of literature on fashion marketing by analyzing the rapidly evolving phenomena of webrooming behavior within the multichannel context of the fashion industry.