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This paper aims to examine how interfirm transactional and relational assets drive firm performance (FP) in digitally integrated supply chains.

The authors combine the Transaction Cost Economics (TCE) and Relational Exchange Theory (RET) frameworks to hypothesize that FP will be a function of Asset Specificity (AS), Digital Technology Usage (DTU) and Collaborative Information Sharing (CIS). In addition, the authors hypothesize that Supply Chain Integration (SCI) will partially mediate the effect of DTU and fully mediate the impact of AS and CIS on FP. A cross-sectional survey of supply chain managers is used to test the hypotheses.

Findings indicate that specific investments in digitally integrated supply chains would increase FP. In addition, SCI fully mediates the relationships between AS and FP and CIS and FP, while SCI partially mediates the influence of DTU on FP.

Managers could strategically engage in the technologies that effectively fit within the firm’s supply chain strategies and seek to develop a pragmatic expertise that enables the effective use of technology in a comprehensive setting.

The study enriches the extant literature by incorporating TCE and RET as contradictory viewpoints on AS and investigating how transactional and relational assets affect FP in digitally integrated supply chains.

The purpose of this paper is to build on recent efforts occurring within business-to-business (B2B) marketing research to advance methodological developments. As phenomena within B2B relationships have become increasingly complex, marketing scholars have begun to point out the limitations associated with correlation-based methodological approaches and highlight the need for new developments in this area. One such development is the fuzzy set qualitative comparative analysis (fsQCA).

This study uses a literature review to examine the use of fsQCA in B2B marketing research.

First, the current manuscript presents the benefits that the application of fsQCA can offer to market researchers investigating B2B phenomena. Second, the paper presents the current state of fsQCA use within B2B marketing. Third, it suggests possible marketing B2B research topics that can be explored using fsQCA.

The study highlights the benefits of fsQCA, presents the current state of fsQCA use within B2B marketing and offers a rich future research agenda for B2B marketing scholars. This agenda can also help spur additional method developments in the discipline.

Strategic planning is an organization’s process of describing its strategy, or direction, and making decisions on allocating its resources to track this strategy. SWOT analysis is one of the most commonly used techniques for strategic planning. SWOT examines the strengths (S) and weaknesses (W) agents of the community together with opportunities (O) and threats (T), for selecting and implementing the best strategy which helps in achieving its goals. The purpose of this paper is to enhance the performance of SWOT analysis regarding the quantitative side of strategies, select the best strategy from different strategies and deal effectively with vague and incompatible information, which occurs usually in actual life.

This study used the neutrosophic analytic hierarchy process (AHP) incorporated with SWOT analysis.

By adding the neutrosophic AHP to SWOT analysis, the performance of SWOT analysis is enhanced through determining the quantitative values and dealing with vague and inconsistent information effectively leading to improved decisions.

The developed integrated methodology is validated in a real-life case of Starbucks company. For the case study of Starbucks company, the proposed model helps in determining different strategic plans and, further, ranking these plans effectively, which will help the company to compete with its competitors and develop itself by obtaining a competitive advantage over its competitors in an uncertain business environment.

In the case study of Starbucks company, the proposed model helps to determine the different strategic plans, rank these plans which help the company compete with its competitors, develop itself and grow.

This research is the first to address SWOT analysis with neutrosophic AHP.

The purpose of this study is to determine if brand passion shapes attitudinal brand loyalty while driving a series of important brand-related outcomes (i.e. brand advocacy, social media following, sense of community, willingness to pay a premium price and alternative devaluation). These aspects are explored for sports apparel brands after considering the perceptions of Iranian consumers.

This study is based on the analysis of survey data gathered online and face-to-face from a sample of Iranian consumers of sports apparel brands that were analysed using partial least square path modelling.

The key empirical findings obtained confirm that brand passion underpins attitudinal brand loyalty and several important brand-related outcomes. Furthermore, the findings show that attitudinal brand loyalty explains the impact of brand passion on most of the outcomes considered, except for social media following.

This study advances knowledge of brand passion by illustrating its “power” as a strong nuance of relationships between consumers and brands. In particular, this study highlights the importance of brand passion in shaping attitudinal brand loyalty, as well as a driver of several outcomes of theoretical and managerial relevance.

By establishing strategies aimed at enhancing brand passion, brand managers can increase attitudinal brand loyalty, attain important goals such as brand advocacy, premium price and social media following, as well as the devaluation of competing brands.

This study uses a unidimensional theorisation of brand passion to increase the understanding of its role as predictor of attitudinal brand loyalty and driver of relevant outcomes. It also examines the mediating effect of attitudinal brand loyalty, thus illustrating important conceptual links between brand passion and brand loyalty in the context of sports apparel brands in a growing economy (Iran).

The primary purpose of this study is to examine the relationship between conumers' emotional attachment towards fashion apps and positive behavioral outcomes, such as e-WoM and repurchase intention. The study also aims to explore how e-servicescape, customer experience and perceived value of online shopping influence this relationships.

The study has used quantitative research methods to collect data from a sample of 484 consumers who had previous experience of purchasing using fashion apps. Data were collected from university students enrolled in university in Gujarat, India using an online self-administered questionnaire. The data are analyzed using structure equation modeling to determine the relationships between the variables under investigation.

The results demonstrate relationships between e-servicescape, customer experience and perceived value of online shopping, emotional attachment and the two consumer outcomes: repurchase intention and e-WoM. The study found support for hypotheses 1, 2 and 3, highlighting the influence of e-servicescape, customer experience and perceived value of online shopping in developing emotional attachment with fashion apps. The study also confirmed hypotheses 5 and 6, which suggest that consumers who have a stronger emotional attachment to fashion apps are more likely to intend to repurchase fashion products and engage in positive electronic word-of-mouth behavior for fashion brands.

In today's digital age, fashion apps are vital for fashion retailers to remain competitive and offer their customers a smooth and immersive shopping experience . Given the potential impact of fashion apps on the customer behavior, it is essential to investigate the relationship relationships between e-servicescape, customer experience and perceived value of online shopping, emotional attachment and the two consumer outcomes: repurchase intention and e-WoM in the context of fashion apps. The findings of the study are expected to contribute to the understanding of consumer behavior in the context of fashion apps and e-commerce more broadly. The results may also provide insights into how fashion retailers can improve their online presence and customer experiences to increase emotional attachment and positive behavioral outcomes.

The results of this study have several implications for online retail managers and fashion app developers. The study provides strong support for the idea that the extent to which online customers feel emotionally attached to fashion apps is strongly related to their e-WoM and repurchase intention. Moreover, the results of the study suggest that online retailers who are looking to cultivate emotional connections with consumers through fashion apps should prioritize three key areas: e-servicescape, customer experience and perceived value of online shopping.

This study investigates the mispricing dynamics of NIFTY 50 Index futures, drawing upon daily data spanning from January 2008 to July 2023.

The study employs both a single regime analysis and a tri-regime model to understand the fluctuations in NIFTY 50 Index futures mispricing.

The study reveals a complex interplay between various market factors and mispricing, including forward-looking volatility (measured by the NIFVIX index), changes in open interest, underlying index return, futures volume, index volume and time to maturity. Additionally, the relationships are regime-dependent, specifically identifying the regime-dependent nature of the relationship between forward-looking volatility and mispricing, the impact of futures volume on mispricing, the effect of open interest on mispricing, the varying influence of index volume and the influence of time to maturity across the three distinct regimes.

These findings offer valuable insights for policymakers and investors by providing a detailed understanding of futures market efficiency and potential arbitrage opportunities. The study emphasizes the importance of understanding market dynamics, transaction costs and timing, offering guidance to enhance market efficiency and capitalize on trading opportunities in the evolving Indian derivatives market.

The Vector Autoregression (VAR) and Threshold Vector Autoregression Regression (TVAR) models are deployed to disentangle the interrelationships between NIFTY 50 Index futures mispricing and related endogenous determinants.

This study investigates the Nifty 50 Index futures mispricing across three distinct market regimes.

We highlight how factors like volatility, futures volume, and open interest vary in their impact.

The study employs vector auto-regressive and threshold vector auto-regressive models to explore the complex relationships influencing mispricing.

We provide valuable insights for investors and policymakers on improving market efficiency and identifying potential arbitrage opportunities.

The Indian marble and stone industry has got the potential to contribute well to the development of the emerging economy. However, unlike the other Indian industries, stone and marble industries are highly underrated sectors, which may become a critical factor for development. This paper analyses the sustainability factors in supply chain management practices.

A literature review is used to identify the barriers and drivers in sustainable supply chain management practices. Interpretive structural modeling has been used to obtain a hierarchy of barriers and drivers along with driving power and dependence power analysis. Further, MICMAC analysis is used for segregating the barriers and drivers in terms of their impact on sustainability.

The findings of the work of this research are that the attention of society, government, and commercial banks should be more toward the unorganized condition of stone and marble sector. There should be an increase in the commitment of stakeholders to reduce pollution and install safety, by enforcing more relevant laws and regulations and creating the importance of environmental awareness.

The main contribution of this research is to identify the barriers and drivers of sustainable supply chain management in a stone and marble industry. The paper proposes a sound mathematical model to prioritize the critical factors for responsible production and consumption of resources from sustainability perspectives of stone industry.

Lean manufacturing (LM) is prevalent in the manufacturing industry; thus, focusing on fast and accurate lean tool implementation is the new paradigm in manufacturing. Value stream mapping (VSM) is one of the many LM tools. It is understood that combining LM implementation with VSM tools can generate better outcomes. This paper aims to develop an expert system for optimal sequencing of VSM tools for lean implementation.

A proposed artificial neural network (ANN) model is based on the analytic network process (ANP) devised for this study. It will facilitate the selection of VSM tools in an optimal sequence.

Considering different types of wastes and their level of occurrence, organizations need a set of specific tools that will be effective in the elimination of these wastes. The developed ANP model computes a level of interrelation between wastes and VSM tools. The ANN is designed and trained by data obtained from numerous case studies, so it can predict the accurate sequence of VSM tools for any new case data set.

The design and use of the ANN model provide an integrated result of both empirical and practical cases, which is more accurate because all viable aspects are then considered. The proposed modeling approach is validated through implementation in an automobile manufacturing company. It has resulted in benefits, namely, reduction in bias, time required, effort required and complexity of the decision process. More importantly, according to all performance criteria and subcriteria, the main goal of this research was satisfied by increasing the accuracy of selecting the appropriate VSM tools and their optimal sequence for lean implementation.

The business enterprises are increasingly focusing on buying and supplying of products and services in a manner to reduce the adverse impacts on the environment, society, and economy. In view of the above, the concept of sustainable supply chain management (SSCM) has received attention of the industry and academia due to its importance on environmental, social and corporate responsibility through economic performance. The paper aims to discuss these issues.

The structured literature review attempts to map the various theories in the SSCM literature from the perspectives of economic performance, environmental dimensions, and social values and ethics.

As supply management is vital for enhancing organizational competitiveness, the present work attempts to investigate the theoretical perspectives in SSCM to develop an understanding of the current research activities and future potentials.

This work aims to gain a number of valid insights for the practitioners and the researchers. It also focuses on the perspectives of governance mechanisms for successful implementation SSCM practices in the business enterprises.

As the theory building initiatives with implications on the conceptualization of SSCM is limited in literature, this work has also been able to identify the trends and relevant research gaps to define the potential areas for future research.

The purpose of this study is to assess the lean performance of a tyre manufacturing firm in India. The key objective is to find key strategic and operational decision‐making dimensions for developing effective lean manufacturing environment in a tyre manufacturing organization.

This research is empirical in nature where the opinions of a group of experts of an Indian tyre manufacturing firm were consulted to formulate an interpretive structural model (ISM) of the critical success factors of lean manufacturing implementation in a tyre manufacturing organization. The authors have developed an Excel‐based template for quantitative assessment of lean performance indicators on the basis of feedback from the operational staff.

This research work suggests that financial capability of an organization drives the top‐management commitment for incorporating lean manufacturing practices in a tyre manufacturing organization. Organizational culture and human resource management are the important enablers for developing change management paradigm, which in turn leads to performance improvement. This study also reveals that over‐processing as well as excessive defects are the most detrimental wastes in radial tyre manufacturing, which accounts for high manufacturing cost of radial tyre manufacturing in India.

Since this study is carried out in a single (case) organization, a relatively small sample size restricts the outcome from being considered for generic industrial application. This study none the less is useful for practicing managers and academicians for the development of lean manufacturing strategy in context with the tyre industry since it encompasses insightful views of experienced lower to upper middle level managers.

This paper provides some key enablers for the successful implementation of lean tools in Indian tyre manufacturing, where lean practices are still in the early stage and little literature is available in this context with tyre manufacturing. Also an attempt has been made to develop a simple Excel‐based template for lean assessment in the tyre industry. This template can be used in other industries by simply modifying the key attributes.