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This paper aims to investigate the firm performance of micro, small and medium enterprises (MSMEs) by using artificial intelligence-based supply chain resilience strategies. A theoretical framework shows the relationship between artificial intelligence, supply chain resilience strategy and firm performance.

A questionnaire is developed to survey the MSMEs of India. A sample size of 307 is considered for the survey. The employees working in MSMEs are targeted responses. The conceptual model developed is tested empirically.

The study found that eight hypotheses were accepted and two were rejected. There are five mediating variables in the current study. Artificial intelligence, the independent variable, positively affects all five mediators. Then, according to the survey and analysis of the final 307 responses from MSMEs, the mediating variables significantly impact the dependent variable, firm performance.

This study is limited to emerging markets only. Also this study used only cross sectional data collection methods.

This study is essential for supply chain managers and top management willing to adopt the latest technology in their organisation or firmfor a better efficient supply chain process.

This study investigated artificial intelligence-based supply chain resilience for improving firm performance in emerging countries like India. This study tried to fill the research gap in artificial intelligence and supply chain resilience.

Managing farm waste is a fundamental problem for farmers with economic, environmental and social impacts throughout the supply chain. Little research has explored innovative product solutions. This paper examines gleaning to reduce farm waste and proposes a resource-based Gleaning Innovation Framework which can lead to differentiated consumer products.

A multi-method approach, including descriptive company reviews, practitioner interviews and consumer surveys, evaluated how different participants in the food supply chain view the farm waste problem and the innovation of products through gleaning.

This research found that practitioners and consumers are cognizant and invested in reducing farm waste, with gleaning as a plausible solution. Future research includes gathering perspectives from retailers and other supply chain members, which may further develop the conceptualization of the gleaning innovation process.

Uniquely, the authors propose the Gleaning Innovation Framework that provides a platform for innovation across the supply chain to reduce farm waste. The research contributes to the farm waste debate with evidence that gleaning can assist the reduction of farm waste through product innovation. Developing innovations to reduce farm waste in sustainable and environmentally friendly ways would not only benefit the supply chain platform but also society.

The purpose of this study is to identify and analyze the barriers associated with the adoption of Industry 4.0 technologies in agricultural supply chains.

The study initially identified thirteen barriers by conducting a literature review and semi-structured interviews with key stakeholders. Subsequently, these barriers were validated and modeled using an integrated Fuzzy Delphi-ISM approach. Finally, MICMAC analysis was employed to categorize the barriers into distinct clusters.

The results provide considerable insights into the hierarchical structure and complex interrelationships between the barriers as well the driving and dependence power of barriers. Lack of information about technologies and lack of compatibility with traditional methods emerged as the two main barriers which directly and indirectly influence the other ones.

The robust hybrid Fuzzy Delphi and ISM techniques used in this study can serve as a useful model and benchmark for similar studies probing the barriers to Industry 4.0 adoption. From a theoretical standpoint, this study expands the scope of institutional theory in explaining Industry 4.0 adoption barriers.

The study is timely for the post-COVID-19 recovery and growth of the agricultural sector. The findings are helpful for policymakers and agriculture supply chain stakeholders in devising new strategies and policy interventions to prioritize and address Industry 4.0 adoption barriers.

It is the first comprehensive, multi-country and multi-method empirical study to comprehensively identify and model barriers to Industry 4.0 adoption in agricultural supply chains in emerging economies.

This study aims to synthesize and analyze research on the Supply Chain Management Practices (SCMPs)-performance nexus, examine current knowledge, identify emerging trends, and provide plausible suggestions for future research engagements in the manufacturing sector in the context of Developing and Emerging Economies (DEEs).

Following a systematic review approach, this study analyzed 20 peer-reviewed scientific journal articles published between 2007 and 2021. The study sample was systematically selected from the Web of Science (WoS) and Google Scholar databases, following strict evaluation and selection criteria.

Numerous dimensions of SCMPs have been considered in the extant literature; however, six have stood out as the most common. In addition, operational performance stood out as the most widely investigated measure in the SCM literature. Moreover, SCMPs have predominantly shown positive effects on performance outcomes. Methodological issues that future studies should consider are suggested.

The sample size was not sufficiently large relative to the rule of thumb set in the literature because of the scarcity of studies in the manufacturing sector in the DEEs context. Despite these limitations, the results of this study provide crucial insights into knowledge and practice.

This review is the first of its kind to examine the SCMPs-performance nexus in the context of DEEs. Based on the findings of this study, future research directions are proposed.

This study aims to examine the performance implications of an information governance (IG) framework for managing, controlling access to and securing information, focusing on (1) the performance benefits of an organization's IG orientation and (2) how the configuration of IG orientation and supply chain (SC) strategy type relate to performance outcomes.

This study leverages multiple secondary sources for US hospitals, serving as the context for the study. It also employs cluster analysis to develop an SC strategy taxonomy, namely sophisticated and delivery-focused SC strategies. The proposed research model is tested using a robust regression to mitigate the influence of outliers and produce more accurate estimates.

IG orientation is positively associated with financial performance and patient experience, and IG-oriented hospitals with a sophisticated SC strategy realize more financial benefits and achieve better patient care experiences compared to other configurations. Regardless of SC strategy type, IG-oriented hospitals offer better care experiences than non-IG-oriented hospitals.

This paper offers empirical evidence that a hospital's IG orientation and SC strategy jointly affect financial outcomes and patient experience. For hospitals, an organization-wide framework for governing information streamlines both intra- and inter-organizational information flows and improves care delivery throughout a patient's care experience.

This is one of a few studies that empirically examine the performance implications of governance of information in the domain of supply chain management (SCM). This study also develops an SC strategy taxonomy for the healthcare context and offers a springboard for research in service SC strategy.

The purpose of this paper is to provide an organizing lens for viewing the distinct contributions to knowledge production from those research communities addressing the impact of competitive strategy on company performance in general, and the influence of cost leadership and differentiation strategy on organizational performance in detail.

The research methodology was based on the PRISMA review, and thematic analysis based on an iterative process of open coding was analyzed and then the sample was analyzed by illustrating the research title, objectives, method, data analysis, sample size, variables and country.

The main factor that influenced the competitive strategy is strategic growth; strategic growth has a significant influence on competitive strategy. Furthermore, competitive strategy will boost firm network, performance measurement and organization behavior. In the same way, the internal goal factor will enhance organizational effectiveness. Also, a differentiation strategy will support management practice factors, strategic positions, product price, product characteristics and company performance.

This study contributes to the literature by identifying a framework of competitive strategy factors, company performance factors, cost leadership strategy factors, differentiation strategy factors and competitive strategy with global market factors. This study provides a complete picture and description of the resulting body knowledge in competitive strategy and organizational performance.

In the aftermath of disasters, humanitarian actors need to coordinate their activities based on accurate information about the disaster site, its surrounding environment, the victims and survivors and the supply of and demand for relief supplies. In this study, the authors examine the characteristics of radio frequency identification (RFID) technology and those of disaster relief operations to achieve information visibility and actor coordination for effective and efficient humanitarian relief operations.

Building on the contingent resource-based view (CRBV), the authors present a model of task-technology fit (TTF) that explains how the use of RFID can improve visibility and coordination. Survey data were collected from humanitarian practitioners in India, and partial least squares (PLS) analysis was used to analyze the model.

The characteristics of both RFID technology and disaster relief operations significantly influence TTF, and TTF predicts RFID usage in disaster relief operations, providing visibility and coordination. TTF is also a mediator between the characteristics of RFID technology and disaster relief operations and between visibility and coordination.

The many recent humanitarian disasters have demonstrated the critical importance of effective and efficient humanitarian supply chain and logistics strategies and operations in assisting disaster-affected populations. The active and appropriate use of technology, including RFID, can help make disaster response more effective and efficient.

Humanitarian actors value RFID technology because of its ability to improve the visibility and coordination of relief operations. This study brings a new perspective to the benefits of RFID technology and sheds light on its antecedents. The study thus expands the understanding of technology in humanitarian operations.

This paper aims to explore the significance of resource sharing in business to capture new market opportunities and securing competitive advantages. Firms enter strategic alliances (SAs), especially for designing new products and to overcome challenges in today’s fast changing environment. Research projects have dealt with the creation of SAs, however without concrete referencing the impact on selected supply chain resources. Furthermore, academia rather focused on elaborating the advantages and disadvantages of SAs and how this affects structural changes in the organization than examining the effects on supply chain complexity and performance.

The authors collected and triangulated a multi-industry data set containing primary data coming from more than 200 experts in the field of supply chain management along and secondary data coming from Refinitiv’s joint ventures (JVs) and SA database and IR solutions’ database for annual reports. The data is evaluated in three empirical settings using binomial testing and structural equation modeling.

The results show that nonequity SAs and JVs have varying degrees of impact on supply chain resources due to differences in the scope of the partnership. This has a negative impact on the complexity of the supply chain, with the creation of a JV leading to greater complexity than the creation of a nonequity SA. Furthermore, the findings prove that complexity negatively impacts overall supply chain performance. In addition, this study elaborates that increased management capabilities are needed to exploit the potentials of SAs and sheds light on hurdles that must be overcome within the supply network when forming a partnership. Finally, the authors give practical implications on how organizations can cope with increasing complexity to lower the risk of poor supply chain performance.

This study investigates occurring challenges when establishing nonequity SAs or JVs and how this affects their supply chain by examining supply networks in terms of complexity and performance.

This research attempted to establish the underlying dimensions of supply chain management practices, blockchain technology and supply chain performance in the Indian dairy industry. Additionally, the study proposes a conceptual model that shows the mediating effects of blockchain technology in the relationship between supply chain management practices and supply chain performance.

Structural equation modelling (SEM) is incorporated to examine the proposed model using SPSS and AMOS version 24. The study population includes 119 registered Indian dairy processing units operating in Uttar Pradesh and New Delhi (source: Dairy – India). Individual registered dairy processing unit's top four executives, that is Head of the Dairy Processing Plant, Supply Chain head and Marketing Head, and IT head are chosen as the respondents of the study, which renders the sample size of 476. Judgmental sampling based on the organisation's market position and plant production capacity (i.e. one lakh litre per day) has been set as the benchmark for selecting the dairy processing units. The executives are selected as respondents as they are well-versed in the phenomenon of supply chain management practices, blockchain technology and supply chain performance compared to other staff working in the dairy industry. The data was collected from December 2021 to March 2022 through judgmental sampling. The target sample size was 476, but only 286 questionnaires were received in a completed state and were further used for analysis.

Manufacturing practices, information sharing, distribution management, inventory management and blockchain technology have a significant and positive impact on supply chain performance in the Indian dairy industry. Furthermore, the research demonstrates that blockchain technology partially mediates the relationship between supply chain management practices and supply chain performance in the context of the Indian dairy industry.

This research is focused on the Indian dairy industry operating in only two states, namely New Delhi and Uttar Pradesh. More research is needed to determine whether SCM practices and the prospects for blockchain technology among channel members are universally applicable to merchants in non-dairy products. Similar investigations should be carried out on dairy industry operating in various formats and in numerous geographic locations. Further, case studies can be conducted by future researchers to learn how supply chain management methods are deployed, what precisely these practices entail and what costs and time demands are required by these practices in context of small independent retailers across different germane expanse.

While the available literature on the research area is spread out, the influence of blockchain technology in the Indian dairy industry has not yet been sufficiently analysed. Therefore, the research article focused on exploring underlying dimensions of the constructs of supply chain management practices, blockchain technology adoption and supply chain performance in the context of the Indian dairy industry.

The purpose of this study is to develop a conceptual framework to understand how industry 4.0 technologies can help firms building supply chain resilience (SCR). With the increasing in turbulent business environment and other disruptive events, firms want to build robust and risk resilience supply chains. The study also explores the role of supply chain visibility (SCV) and environmental dynamism (ED) on the relationship between Industry 4.0 and SCR.

Survey data from 354 firms designated by the Indian Ministry of Petroleum and Natural Gas, as well as organizations that work with these oil and gas firms was analyzed with structural equation modelling, hierarchical linear regression and necessary conditions analysis.

The findings reveal that Industry 4.0 base technologies enable firms to develop and exploit SCV to build SCR. Furthermore, Industry 4.0 base technologies substantially correlate with SCV under the differential effect of ED, improving SCR.

The cross-sectional data restrict the generalizability of the findings to other geographies and sectors.

This study can assist managers in making well-informed decisions about the strategic use of technology to increase SCV and foster resilient supply chains.