Search

Corporate entrepreneurial leadership (CEL) plays a critical role in promoting innovative behavior that disrupts existing practices in organizations, to say the least, encouraging new policy initiatives that could affect the business and social performance of the organizations under their sustainable development goals (SDGs). CEL can help achieve SDGs by redesigning different contextual factors to help promote various policy initiatives. In this vein, this study identifies the factors which could improve the business and social performance of the organizations helping to achieve SDGs through an amalgam of theoretical lenses, particularly the dynamic capability view. Based on extant literature, we developed, validated, and applied a theoretical model using the partial least square structural equation modeling technique on data collected from 327 respondents from different organizations. The study found that CEL capability significantly and positively impacts the various organizational entities and resources, which in turn affects the business and social performance of the organizations. Theoretical and managerial implications of the findings are also discussed. [ABSTRACT FROM AUTHOR]

Artificial Intelligence (AI) offers a promising solution for building and promoting more resilient supply chains. However, the literature is highly dispersed regarding the application of AI in supply-chain management. The literature to date lacks a decision-making framework for identifying and applying powerful AI techniques to build supply-chain resilience (SCRes), curbing advances in research and practice on this interesting interface. In this paper, we propose an integrated Multi-criteria decision-making (MCDM) technique powered by AI-based algorithms such as Fuzzy systems, Wavelet Neural Networks (WNN) and Evaluation based on Distance from Average Solution (EDAS) to identify patterns in AI techniques for developing different SCRes strategies. The analysis was informed by data collected from 479 manufacturing companies to determine the most significant AI applications used for SCRes. The findings show that fuzzy logic programming, machine learning big data, and agent-based systems are the most promising techniques used to promote SCRes strategies. The study findings support decision-makers by providing an integrated decision-making framework to guide practitioners in AI deployment for building SCRes. [ABSTRACT FROM AUTHOR]

This study aims to analyse the manufacturer-supplier relational perspective under the influence of exogenous financial risk. Following corporate finance theory, a multi-objective decision model for supplier selection and order allocation is developed to maximise the total profit of the manufacturer, and minimise the implicit equity stake and financial risk faced by selected suppliers. A two-echelon supply chain is explored under the influence of foreign exchange risk, default risk, market risk and price fluctuation risk, and solved using an NSGA-III algorithm. Three case scenarios are analysed to explore the influence of a set of financial risk on the manufacturer-supplier relationship and the behaviour of suppliers concerning risk profile, both in the short and long-term horizon. The results are analysed from both the manufacturer as well as supplier perspective, and the optimal conditions are discussed under the cascading risk circumstances. The study provides multiple insights into the impact of financial risk on supply chain relationship and will be valuable for dealing with similar uncertain economic environment. The research is likely to be of benefit beyond supply chain managers, like investors and financial risk managers in making informed decisions. The need to focus on systemic risk in supply chains is evident from the study. [ABSTRACT FROM AUTHOR]

Overthinking refers to the process of dwelling on thoughts and ideas for an extended period of time, often leading to a feeling of mental exhaustion and anxiety. It involves analyzing and interpreting situations and events in excessive detail and repeatedly replaying scenarios in one's mind. We found that people who are experiencing an overthinking issue, are unable to make tough life decisions or when they are dealing with insecurities. Causes of this mental clutter are daily stress, the paradox of choices, too much stuff, and the negativity bias. We also found the SMART (which stands for Specific, Measurable, Attainable, Relevant, and Time-bound) goals design approach during our literature study. Through our research paper, we try to solve this issue by employing Design Research Methodology (DRM). During this DRM, we did secondary research, conducted interviews with stakeholders as a part of our primary research, and talked with psychologists to deepen our knowledge in this domain which helped us to define our target users. The outcome of this research was a mobile application that aims to assist overthinkers in social interaction and achieving their individual goals while also assisting them to reframe their cognitive processes. [ABSTRACT FROM AUTHOR]

The present study investigates use of blended concept map technique applied to the thermodynamics in the second year of Mechanical engineering of University of Mumbai, India. Two studies have been designed. In one study, traditional teacher leaning was followed to learn the topic of thermodynamics and in another study, students taught the same topic with concept map using software. The present work shows that there is significant difference between test score of pre and posttests who uses concept maps. Students showed positive inclination towards use of concept maps. [ABSTRACT FROM AUTHOR]

Multi-tier sustainable supply chain management (MT-SSCM) is increasingly attracting a great deal of interest in academia and practice. However, attention to social sustainability has been relatively limited, and the initiatives of implementing social sustainability, especially in low-tier suppliers in supply chains, are facing enormous barriers and obstacles. The central aim of this paper is to investigate the obstacles that hinder the adoption of social sustainability in the multi-tier supply chain (MT-SC) and prioritise the most effective solutions to promote the adoption of this critical concept. Therefore, we based an extensive literature review on identifying the most relevant barriers and solutions to social sustainability adoption in MT-SC. Moreover, we propose a hybrid and multi-context methodology based on hesitant fuzzy sets (HFS), cumulative prospect theory (CPT) along with VIKOR to identify the most prominent barriers and solutions for three supply-chain sectors, i.e. chemical, agri-food, and textile. The results indicate that solutions to social sustainability in MT-SC are sensitive to the supply chain sector. However, there is a general trend toward adopting emerging technologies and openness and transparency-based relationships with the external environment. Managers could use these results to redirect their strategies to promote social sustainability, particularly in low-tier suppliers in under-developed countries. [ABSTRACT FROM AUTHOR]

Blockchain technology (BT) is a disruptive technology to achieve sustainable supply chain performance. The previous literature suggests a slow rate of BT adoption in improving sustainable supply chain performance (SSCP) in the agriculture context. This study explores and evaluates barriers and enablers to the adoption of BT for SSCP in e-enabled agriculture supply chains. using a novel hybrid technique integrating the Pythagorean Fuzzy sets (PFS), Cumulative Prospect Theory (CPT), and VIKOR. Data was collected data from 215 agriculture firms in Asia and North Africa. The results presented strategies for implementing BT for SSCP in e-agriculture supply chains and recommended (1) developing transparency readiness in sustainability, (2) collaboration among supply chain partners, (3) upgrading data access control (4) management commitment (5) collaboration with governments. The study presents several implications to managers to redirect strategies and focus efforts on the most significant enablers to promote BT implementation for SSCP in e-enabled SSCP. [ABSTRACT FROM AUTHOR]

In a highly competitive and changing environment, manufacturers are called to adopt the paradigms of smart, sustainable, resilient, and lean manufacturing (SSRL). However, despite the growing interest in the topic and the potential of smart manufacturing features to enable sustainable development, little is known about these interactions in the system of SSRL. Therefore, to address this gap, this study investigates the moderating effect of SM on lean manufacturing and resilient manufacturing for SP while examining the existing relationship between lean and resilience. Drawing upon a hybrid methodology including the partial least squares‐structural equation modeling (PLS‐SEM) and machine learning algorithms, this research paper develops and tests the hypothetical model using collected data from 399 organizations in China, Africa, and Europe. The findings reveal important implications regarding the fostering effect of SM on the components of the SSRL system and how firms can be both lean and resilient and achieve high sustainable performance simultaneously. [ABSTRACT FROM AUTHOR]

3D printing is estimated to play a significant role in offering tangible and commercial benefits to the supply chains. 3D printing application in food is becoming more complex and flexible putting pressure on printing companies. 3DP of food is expected to help in controlling the quality of food products, reduce waste, and increase food variety. Despite the vast potential of 3DP of food, the adoption is still in its nascent stage. Therefore, this study attempts to identify the various barriers that affect the adoption of 3DP in the food industry. The study identifies and investigates the interdependencies between 3D food printing implementation barriers for sustainable food supply chains. The hybrid 'interpretive structural modeling (ISM) and decision-making trial and evaluation laboratory (DEMATEL)' methodology was employed to understand the hierarchical and contextual relationships between the identified barriers. Thirteen barriers were identified and validated by food printing experts. The cost of consumables was identified as a major barrier to implementing 3D food printing in supply chains. We also identified linkage barriers and dependent barriers. Our findings put forward suggestions for overcoming some of the implementation barriers, helping to advance the development of sustainable 3D food printing-based supply chains. [ABSTRACT FROM AUTHOR]

For several reasons, recent attention has focused on urban agriculture in the context of sustainable and smart agriculture. Most of the global population has relocated from rural to urban areas. The ecological impact of agriculture is a rising concern. Furthermore, food insecurity, particularly food availability, remains a significant issue. Satisfying rising food demand with minimal environmental impact is a significant barrier to more sustainable food production. In this article, we study a sustainable location for urban farming that optimally balances economic and environmental objectives. We formulate the problem as a multi‐objective linear program that considers maximizing the ecological benefit and crop production yield and minimizing transportation cost, sensor cost, and CO2 emissions. The proposed mathematical model is then solved using a two‐phase method. The first phase uses several multi‐objective optimization (MOO) methods (weighted sum, epsilon‐constraint, augmented epsilon) to generate a pool of compromise solutions. The second phase uses multi‐criteria decision‐making (MCDM) methods (MARCOS, VIKOR, and Possibility Degree) to rank compromise solutions. We performed a sensitivity analysis first by studying the effect of different criteria weights (balanced, environmentally, and economically oriented) and then by investigating the rank reversal. Furthermore, we developed a thorough validity test that examines the impact of the dynamic elements of rank reversal by changing the importance of the model's input parameters. To provide a fusion ranking of the MCDM rankings, we devised an aggregated ranking approach using the half‐quadratic (HQ) method. [ABSTRACT FROM AUTHOR]

The use of digital technologies such as 'internet of things' and 'big data analytics' have transformed the traditional retail supply chains into data-driven retail supply chains referred to as 'Retail 4.0.' These big data-driven retail supply chains have the advantage of providing superior products and services and enhance the customers shopping experience. The retailing industry in India is highly competitive and eager to transform into the environment of retail 4.0. The literature on big data in the supply chain has mainly focused on the applications in manufacturing industries and therefore needs to be further investigated on how the big data-driven retail supply chains influence the supply chain performance. Therefore, this study investigates how the retailing 4.0 context in India is influencing the existing supply chain performance measures and what effect it has on the organisational performance. The findings of the study provide valuable insights for retail supply chain practitioners on planning BDA investments. Based on a survey of 380 respondents selected from retail organisations in India, this study uses governance structure as the moderating variable. Implications for managers and future research possibilities are presented. [ABSTRACT FROM AUTHOR]

The current literature claims the direct effects of industry 4.0 technologies (I4 T) on lean manufacturing practices (LMP) and sustainable organisational performance (SOP). LMP are also found to have a positive influence on SOP. However, the integrated effect of I4 T and LMP on SOP has not been empirically investigated. To address this gap, this research study investigates the indirect effects of I4 T on SOP with LMP as the mediating variable; furthermore, it aims to confirm or not the direct effects of I4 T on LMP and SOP. The study is based on data collected from 205 managers, working in 115 manufacturing firms. The findings suggest significant direct and indirect effects of I4 T on SOP and confirm the presence of LMP as a strong mediating variable. The results of the study extend the literature on I4 T by identifying I4 T as an enabler of LMP, leading to enhancement of the SOP. Implications and future research directions for academicians, practitioners, and consultants are provided. [ABSTRACT FROM AUTHOR]

Performance measures and metrics (PMM) is identified to be an essential aspect of managing diverse supply chains. The PMM improves the firm's performance by providing open and transparent communication between the various stakeholders of an organisation. The literature suggests that big data analytics has a positive impact on the supply chain and firm performance. Presently, the literature lack studies that recognise the PMM relevant to big data-driven supply chain (BDDSC). The present study is based on a comprehensive review of 66 papers published with the primary objective to identify the various PMMs used to evaluate the BDDSC. The findings suggest that the PMMs applicable to BDDSC can be classified into two non-mutually exclusive categories. The first category represents 24 performance measures used to evaluate the performance of the big data analytics capability and the second category represents 130 measures used for assessing the performance of BDDSC processes. The study also reports the emergence of new performance measures based on increasing use of predictive and social analytics in BDDSC. Based on the results of the study a framework on BDDSC performance measurement system is proposed which will guide the managers to have a robust performance measurement system in their organisation. [ABSTRACT FROM AUTHOR]

The focus of Industry 4.0 (I4) technologies is to address the issue of scarce resources and improve productivity by providing solutions to economise the use of limited resources and find other substitute raw materials. Circular economy (CE) is also identified as a solution to manage the increasing pressure of environmental regulations, price volatility in resources, and supply uncertainty. However, the relationship between I4 technologies, CE and sustainable performance (SP) is still unexplored and demands a more conceptual and empirical investigation on understanding how the I4 technologies favour the transition towards CE practices and what impact they have together on SP. Based on a survey of 238 manufacturing practitioners from India, the study investigates the mediating and moderating role of CE practices on the relationship between I4 technologies and SP. The findings reveal that developing an environment of CE is not a prerequisite for implementing I4 technologies. However, I4 technologies support developing efficient CE environment, which, leads to the achievement of sustainable organisational goals. Future research directions and implications for practitioners are provided. [ABSTRACT FROM AUTHOR]

The advent of new technologies alongside the generation of the vast amount of data in the manufacturing processes makes Green Lean Six Sigma (GLSS) approaches very challenging. This paper presents a novel framework termed 'BDA-GLSS' that guides companies to effectively integrate Big Data Analytics (BDA) in GLSS to improve their environmental performance. The BDA-GLSS framework is validated using an industrial case study of a leading chemical company. The results suggest measurable benefits of the proposed framework in enhancing technological readiness, problem identification, and analysis with predictive capability. The BDA-GLSS guides the implementation of BDA techniques within the GLSS framework offering real-time quality control, event-based inspection, and predictive maintenance. The BDA-GLSS enhances the environmental capability, process performance and provides a new perspective for researchers and practitioners to support GLSS projects in achieving higher green performance. [ABSTRACT FROM AUTHOR]