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This paper aims to investigate the effect of governance – a proxy for network effects on small and medium enterprises (SME) growth through access to new markets. Specifically, investigate how export intensity (EI) and performance are affected. This study also tests related theories, given the growth in the post-liberalization setting of a developing economy. Specifically, this study tests Uppsala and born global (BG) perspectives for internationalization and resource-based view for performance.

The authors collect secondary data for each SME over a 20 year period from a growth-oriented developing economy – India. This period is after the liberalization of the Indian economy. Thus, the authors test the hypotheses in this context. The authors expect that exports would surge for SMEs given the governance structures considered. The authors consider several governance modes and two types of product classifications, namely, products and services.

The authors find conditional support for the two models – indicating that governance structures do not consistently support finding new markets. Further, given the governance structure, EI is not consistently a means to improved performance. This is contrary to the expectations. However, at the same time, the authors do find evidence that governance matters and affects products and services differently.

While the authors conduct research in India which has a variety of cultures and state policies, the authors still believe comparative study with multi-country data from developing countries might bring further insights. Further, primary data would also help to understand governance and motivational effects (the authors did not consider the later). Implications: The authors believe the research will have implications for policy since the authors find effects of governance. Hence, specific policies that improve the performance of a governance type could be adopted.

Although SMEs are affected by many factors, the authors find significant effects for important variables. Hence, the authors believe the government could use the study to design proper policies so that new markets could be discovered through different governance forms, through strategic investment and capacity building.

SMEs are a key part of the social fabric of a society/country. The work deals with how SMEs could be helped. Hence, the authors believe the work has important implications for society. Further, as the work deals with large firm-SME interfaces, the authors also inform how these different governance structures are performing and where attention is needed.

The authors find that certain governance-type and SME-type work well together. Further, networks through the governance structures help find new markets – depending on SME-type. The authors find partial support for the Uppsala model and also for the BG model, again depending on the SME-type.

The purpose of this paper is to identify various factors influencing additive manufacturing (AM) implementation from operational performance in the Indian manufacturing sector and to establish the hierarchical relationship among them.

The methodology includes three phases, namely, identification of factors through systematic literature review (SLR), interviews with experts to capture industry perspective of AM implementation factors and to develop the hierarchical model and classify it by deriving the interrelationship between the factors using interpretive structural modeling (ISM), followed with the fuzzy Matrice d’Impacts Croisés Multiplication Appliqués à un Classement (MICMAC) analysis.

This research has identified 14 key factors that influence the successful AM implementation in the Indian manufacturing sector. Based on the analysis, top management commitment is an essential factor with high driving power, which exaggerates other factors. Factors, namely, manufacturing flexibility, operational excellence and firm competitiveness are placed at the top level of the model, which indicates that they have less driving power and organizations need to focus on those factors after implementing the bottom-level factors.

Additional factors may be considered, which are important for AM implementation from different industry contexts. The variations from different industry contexts and geographical locations can foster the theoretical robustness of the model.

The proposed ISM model sets the directions for business managers in planning the operational strategies for addressing AM implementation issues in the Indian manufacturing sector. Also, competitive strategies may be framed by organizations based on the driving and dependence power of AM implementation factors.

This paper contributes by identification of AM implementation factors based on in-depth literature review as per SLR methodology and validation of these factors from a variety of industries and developing hierarchical model by integrative ISM-MICMAC approach.

The purpose of this paper is to differentiate the empowering influences of critical enablers of supply chain management (SCM) along with their interrelationships. These empowering enablers are significant, as they encourage productive execution to improve organizational performance and stakeholder's satisfaction.

From the literature review, incidence of a number of SCM enablers were found and they were subjected to critical scrutiny by a considerable number of experts engaged in SCM research and application to identify significant and applicable empowering enablers by grounded interactions. By using Impact Matrix Cross-Reference Multiplication Applied to a Classification analysis, the driving and dependence power were analyzed and the empowering enablers were ordered. This was pursued by building up a structural model of the empowering enablers using interpretive structure modeling, followed with measuring cause–effect relationship using decision-making trial and evaluation laboratory (DEMATEL).

Among these identified enablers of SCM, operational performance, green SCM, employee empowerment and motivation and strategic association came out to be strategic enablers.

The findings may help the practicing professionals to develop clarity in understanding of these essential enablers and their contextual as well as cause–effect relationship in SCM. The practicing professionals need to focus on all these enablers during implementation of SCM for enhancing the organizational performance and stake holders' satisfaction.

This study is of practical utility in real-life implementation of SCM. The algorithm used in applying the multi-criteria decision-making approach is very user-friendly, and the application of DEMATEL is an innovation compared to previous research. Further, the findings can be used as a benchmark for improving the performance of SCM by considering the cause–effect relationship.

This study focuses on Aaker's Brand Equity Model, to check the effect of brand equity determinants on booking intention (BI) for ridesharing in India. The study also explores the moderation of ecologically conscious consumer behavior (ECCB) on the multiplicative effect of brand awareness (BAw), brand association (BA) and perceived quality (PQ) in influencing the BI.

Responses from 393 Indian ridesharing users were collected using judgmental sampling and were analyzed using Hayes Process macro.

The study found a direct relationship between BAw and BI, BAw and BA, BAw and PQ, BA and PQ, PQ and BI, and BA and BI. Findings revealed mediation of BA in BAw and BI relationship and PQ in BAw and BI relationship. Results revealed that BA and PQ serially mediate BAw and BI relationship. ECCB moderates PQ and BI relationship but not BAw and BI relationship.

Serial mediation and moderated-mediation results draw various theoretical implications for determinants of Aaker's Brand Equity model and ECCB.

The research has several implications for managers in view of brand equity determinants and ECCB. The study also contributes to policy implications.

Study's novel contributions are mediation, serial mediation between brand equity determinants, and moderation of ECCB between BAw and BI for ridesharing.

This paper aims to identify, prioritise and explore the relationships between the various barriers that are hindering the machine learning (ML) adaptation for analysing accident data information in the Indian petroleum industry.

The preferred reporting items for systematic reviews and meta-analysis (PRISMA) is initially used to identify key barriers as reported in extant literature. The decision-making trial and evaluation laboratory (DEMATEL) technique is then used to discover the interrelationships between the barriers, which are then prioritised, based on three criteria (time, cost and relative importance) using complex proportional assessment (COPRAS) and multi-objective optimisation method by ratio analysis (MOORA). The Delphi method is used to obtain and analyse data from 10 petroleum experts who work at various petroleum facilities in India.

The findings provide practical insights for management and accident data analysts to use ML techniques when analysing large amounts of data. The analysis of barriers will help organisations focus resources on the most significant obstacles to overcome barriers to adopt ML as the primary tool for accident data analysis, which can save time, money and enable the exploration of valuable insights from the data.

This is the first study to use a hybrid three-phase methodology and consult with domain experts in the petroleum industry to rank and analyse the relationship between these barriers.

Governance is the key to establishing effective collaboration among humanitarian logistics partners addressing an ongoing relief work. With a focus on humanitarian interorganizational collaboration, this research draws on governance theories to investigate how conflicts can be mitigated in this challenging setting.

The focus on governance extends attention to the frontiers of contractual agreement, trust and environmental uncertainty to be applied in the humanitarian setting. To develop perspectives, an online survey of 289 field executives working in humanitarian organizations across the globe is conducted. The findings are based on hierarchical regressions.

Environmental uncertainty, in humanitarian logistics, is not straightforward, but wields distinctive challenges in the response phase (immediate to the disaster) as well as the recovery phase (beginning of build back) – to loom prospects of conflict between partners. Findings outline that contractual agreement can increase conflict during the response phase (high environmental uncertainty), but mitigate it during the recovery phase (low environmental uncertainty). Furthermore, contractual agreement interactively strengthens the ability of trust to reduce conflict. Yet, trust acting alone shows best outcome to mitigate conflict.

Contrary to the established understanding in traditional logistics suggesting the vitality of contracts to easily mitigate challenges posed by environmental uncertainty, the humanitarian setting extends a unique outset for interorganizational governance based on the temporality of response and recovery phases.

This research pioneers to quantitatively examine the setting of humanitarian logistics based on survey. Given the difficulty of data acquisition, the extant research has largely relied on qualitative investigations when considering the agenda of governance.

Supply chain traceability and supply chain visibility have become a critical element for the effective management of contemporary complex supply chains. At their core is information sharing, which has been acknowledged as a key prerequisite for logistics and supply chain performance, but whose notional underpinnings have not been delineated fully, leading to interchangeable deployment of these terms. Addressing the shortcoming, this paper aims to establish a contrast between the two notions.

Drawing from systematic review protocols, a multi-disciplinary review scope is constructed wherein the synthesis is strategized to primarily channel implications for the scholarship of logistics and supply chain management. The review is aimed at addressing two research objectives: (1) how the notions of traceability and visibility in supply chain management develop contrast in terms of their thematic emphasis and (2) to attain an integrative understanding of the notional convergence and divergence between supply chain traceability and visibility for raising strategic recommendations.

The review outcomes help contrast both the convergence and the divergence between traceability and visibility in the supply chain environment, and the differentiated but fundamental role that information sharing plays within these notions to outline why they are not interchangeable.

The originality of the findings lies in the conceptual synthesis of the relevant literature from both technological and non-technological perspectives to ultimately draw logistics and supply chain management implications. The review also points out key strategic considerations to demarcate the notional boundaries of traceability and visibility in future research.

In the uncertain business environment, the supply chains are under pressure to balance routine operations and prepare for adverse events. Consequently, this research investigates how artificial intelligence is used to enable resilience among supply chains.

This study first analyzed the relationship among different characteristics of AI-enabled supply chain and how these elements take it towards resilience by collecting the responses from 27 supply chain professionals. Furthermore, to validate the results, an empirical analysis is conducted where the responses from 231 supply chain professionals are collected.

Findings indicate that the disruption impact of an event depends on the degree of transparency kept and provided to all supply chain partners. This is further validated through empirical study, where the impact of transparency facilitates the mass customization of the procurement strategy to Last Mile Delivery to reduce the impact of disruption. Hence, AI facilitates resilience in the supply chain.

This study adds to the domain of supply chain and information systems management by identifying the driving and dependent elements that AI facilitates and further validating the findings and structure of the elements through empirical analysis. The research also provides meaningful implications for theory and practice.

The purpose of this study is threefold, which is as follows: investigate the mediating effect of brand fan page attractiveness on the relationship between user gratifications and customer engagement with brand fan pages, determine whether fan page agility moderates this effect and examine the influence of fan page engagement on customers' share of wallet and resistance to negative brand information.

By using an online questionnaire, 614 valid responses were obtained from the followers of multiple Facebook brand fan pages. Partial least squares-structural equation modelling (PLS-SEM) was used to analyse the data.

The results indicate that fan page attractiveness mediates the relationship between user gratifications and fan page engagement. However, this relationship is moderated by fan page agility. Fan page engagement increases customers' share of wallet and resistance to negative brand information. This finding suggests that creating fan page content and interactions that are attractive to customers is not sufficient for promoting engagement; brand fan pages must also be agile to customers' changing needs and competitors' moves.

By proposing and testing a novel moderated mediation effect, this study enriches the uses and gratifications theory (UGT) and provides new insights into the underlying mechanisms and boundary factors driving fan page engagement. In addition, this study contributes to the customer engagement literature by introducing share of wallet and resistance to negative brand information as outcome variables.

Manufacturing companies are increasingly using green smart production (GSM) as a tactic to boost productivity since it has a number of advantages over conventional manufacturing methods. It costs a lot of money and takes a lot of work to create an SMS since it combines a lot of different technologies, including automation, data exchanges, cyber-physical systems (CPS), artificial intelligence, the Internet of things (IoT) and semi-autonomous industrial systems. Green smart manufacturing (GSM) activities provide the foundation for creating ecologically friendly and green products. However, there are a number of other significant barriers obstacles to GSM deployment. As a result, removing this identification of these hurdles in a systematic manner should be a top focus of this study.

This article seeks to identify and prioritize the nine barriers based on research and expert viewpoints on GSM challenges. The analytical hierarchy process (AHP) is used to prioritize the barriers.

The result depicts that, financial constraints is the most important barrier that followed by scarcity of dedicated suppliers, concern to data security lack of understanding of the surroundings, inadequate top management commitment, proper handling of data interfaces lack of support by government, employees' lack of training, concern to data security lack of environment knowledge, fear of change/resistance and constraints of technology.

The current research will help the manufacturing industry in Industry 4.0 to identify potential barriers to GSM implementation.

Green manufacturing (GM) entails the implementation of renewable production methods and eco-friendly procedures in manufacturing businesses. This study helps manufacturers come up with recycling and creative products, and manufacturers can give back to the environment by protecting natural areas by getting rid of the obstacles that get in the way.