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The purpose of this paper is to reduce the post-harvest loss occurring through respiration and CO₂ emission produce by the selected produces, during logistics. This paper proposes a supply chain (SC) structure for the Indian traditional agriculture SC planning model to reduce post-harvest loss and mixed closed transportation to reduce CO₂ emission.

The Indian agriculture SC structure is modeled and solved by genetic algorithm using a MATLAB Optimization toolbox. The respiration rate is measured by a static method. These values are applied in an SC planning model and the post-harvest loss and its corresponding CO₂ emission are estimated.

This paper proposes a supply structure for the Indian traditional agriculture SC to reduce the post-harvest loss; the experiments measured the respiration rate to estimate the CO₂ emission. The mixed closed transportation method is found to be suitable for short-purpose domestic transportation.

The optimized supply structure leads to unemployment through eliminating the intermediaries. Therefore, further research encourages the conversion of intermediaries into hub instead of eliminating them.

This paper includes implications for the development of Indian traditional agriculture SC by an optimized supply structure and novel transportation method for the selected agriculture produces based on compatibility.

This paper identified that the agriculture produces respiration can also emit the CO₂. The closed transportation method can reduce the CO₂ emission of produces respiration than traditional open transportation.

This research seeks to explore the intersection between modularity and conformity in organizational contexts. Modularity, a cornerstone of organizational design, pertains to the decomposability of tasks within an organization into subtasks with internal interdependence and external independence. Conformity, on the other hand, is the adjustment of an individual’s behavior to match that of others, often driven by a desire to adhere to social norms.

We employ agent-based modeling and simulation as a technique to model organizations as complex systems. This approach allows us to delve into the effects of modularity in organizational structures on organizational performance, with a particular emphasis on the role of conformity in this relationship. We treat conformity as exogenously given, which allows us to focus on its effects rather than its emergence.

The results demonstrate that a concentration of interdependent tasks within fewer departments can boost overall performance. Conformity decreases performance in all organizational structures except for cases when the departments work on highly similar tasks. This decline in performance can also explain why functional organizational structures are still being used in practice even though they are less modular than divisional structures — they feature lower levels of conformity and, thus, face smaller decline. Finally, we find that in highly complex settings, organizational performance can, surprisingly, be improved as complexity within departments increases.

To the best of our knowledge, this study is the first to explore the modularity in organizational structures in presence of conformity. Distinctively, we adapt the NKCS model from evolutionary biology to our study, and perform an exhaustive analysis by examining all possible combinations of parameters that refer to the task allocation within organizations. We thereby contribute a unique perspective to the discourse on organizational theory and behavior.

Drawing upon the importance of research and development (R&D) alliances in driving firm innovation performance, extant research has analyzed individually the impact of R&D alliance partner attributes on firm innovation performance. Despite such analyzes, research has generally underestimated the configurations of partner attributes leading to firm innovation performance. This research gap is interesting to explore, as firms involved in R&D alliances usually face a combination of partner attributes. Moreover, gaining a better understanding of how R&D partner attributes tie into configurations is an issue that is attracting particular interest in coopetition research and alliance literature. This paper aims to obtain a better knowledge of this underrated, but important, aspect of alliances by exploring what configurations of R&D alliance partner attributes lead firms involved in R&D alliances to achieve high innovation performance. To tackle this question, first, this study reviews the extant literature on R&D alliances by relying on the knowledge-based view of alliances to identify the most impactful partner attributes on firms’ innovation performance. This paper then applies a fuzzy set qualitative comparative analysis (fsQCA) to explore the configurations of R&D alliance partner attributes that lead firms involved in R&D alliances to achieve high innovation performance.

This study selects 27 R&D alliances formed worldwide in the telecom industry. This paper explores the multiple configurations of partner attributes of these alliances by conducting a fsQCA.

The findings of the fsQCA show that the two alternate configurations of partner attributes guided the firms involved in these alliances to achieve high innovation performance: a configuration with extensive partner technological relatedness and coopetition, but no experience; and a configuration with extensive partner experience and competition, but no technological relatedness.

The research highlights the importance of how partner attributes (i.e. partner technological relatedness, partner competitive overlap, partner experience and partner relative size) tie, with regard to the firms’ access to external knowledge and consequently to their willingness to achieve high innovation performance. Moreover, this paper reveals the beneficial effect of competition on the innovation performance of the firms involved in R&D alliances when some of the other knowledge-based partner attributes are considered. Despite these insights for alliance and coopetition literature, some limitations are to be noted. First, some of the partners’ attributes considered could be further disentangled into sub-partner attributes. Second, other indicators might be used to measure firms’ innovation performance. Third, as anticipated this study applies fsQCA to explore the combinatory effects of partner attributes in the specific context of R&D alliances in the telecom industry worldwide and in a specific time window. This condition may question the extensibility of the results to other industries and times.

This study also bears two interesting implications for alliance managers. First, the paper suggests that R&D alliance managers need to be aware that potential alliance partners have multiple attributes leading to firm innovation performance. In this regard, partner competitive overlap is particularly important for gaining a better understanding of firm innovation performance. When looking for strategic partners, managers should try to ally with highly competitive enterprises so as to access their more innovative knowledge. Second, the results also highlight that this beneficial effect of coopetition in R&D alliances can be amplified in two ways. On the one hand, when the partners involved in the alliance have not yet developed experience in forming alliances. Partners without previous experience supply ideal stimuli to unlock more knowledge in the alliance because new approaches to access and develop knowledge in the alliance could be explored. On the other hand, this paper detects the situation when the allied partners are developing technologies and products in different areas. When partnering with firms coming from different technological areas, the knowledge diversity that can be leveraged in the alliances could drive alliance managers to generate synergies and economies of scope within the coopetitive alliance.

Extant research has analyzed individually the impact of R&D alliance partner attributes on firm innovation performance but has concurrently underestimated the configurations of partner attributes leading to firm innovation performance. Therefore, this paper differs from previous studies, as it provides an understanding of the specific configurations of R&D alliance partner attributes leading firms involved in R&D alliances to achieve high innovation performance.

This paper presents the concerns in manufacturing supply chain. Further this study investigates the role of information technology (IT) and information sharing (IS) in manufacturing supply chain and determines its impact towards supply chain integration (SCI), supply chain performance (SCP), and manufacturing firm performance (FP) in Malaysia. The theoretical framework was proposed for the study on the basis of existing literature. The study administered a survey questionnaire to collect data from manufacturing firms in Malaysia with 112 respondents. A multiple regression analysis is conducted to establish the relationship between IT, IS, SCI, and FP. The study finds that IT and sharing has significant positive effect towards and performance. Firms that use IT and practice IS across partners in the supply chain are more likely to integrate their internal and external value chain for better performance both within and across the manufacturing firms in the supply chain. This study can be of interest to the manufacturing industry as well as other industry practitioners interested in improving the performance of the organization and supply chain in total. For supply chain practitioners, this results indicate that the firms should adopt IT and IS practices to strategically improve SCI. This in turn will also improve the supply chain network and firm’s performance. This study employs a newly developed framework which depicts the causal relationship between IT, IS, SCI, Supply Chain Performance, and FP in Malaysia. Furthermore, it closes a gap in existing literature by examining the effect IT and communication (ICT) practices toward manufacturing firms’ performance and SCP in a single setting. In addition, the current study attempted to construct a model which would estimate and interpret SCP and FP simultaneously, and to evaluate this model in an empirical fashion.

A network of partners helps and assists a crowdfunding platform (CFP) in scouting, assessing and selecting projects. This cooperation increases the number of successful projects by attracting a sizable number of investors, proponents and attracting marginal investors when a campaign falls short of the threshold for success. This study examines the role of partner networks in a platform ecosystem, specifically in terms of number of different partners and their diversity in the performance of the crowdfunding campaign.

Using logistic and linear regressions, we analyze a sample of 233 projects, both funded and not funded, launched by 10 Italian equity CFPs between 2014 and 2018.

Our findings indicate that the variety of partners in a platform's network influence the probability of campaign success and how much capital the proponent company raises. CFPs are resource-constrained new ventures, and a network with a wider variety of partners ensures the strategic resources and competencies that are required in an early stage market, thus facilitating campaign funding.

The variety of partner networks could help CFPs to offer unique and strategic value propositions and define the competitive positioning of platforms.

This study provides a deeper understanding of the determinants of equity crowdfunding campaign performance by emphasizing the role of CFP's network of partners on the entire crowdfunding ecosystem and its underlying organizational elements.

Maintaining food safety techniques in the supply chain management require special food safety labelling techniques during distribution in the retail food industry. The food products have to be of good quality and labelling inbound, manufacturing, and outbound in the supply chain contributes to this aim. The purpose of this study is to evaluate how food safety labelling is managed in Vietnam’s retail food industry with a special focus on food in Ho Chi Minh City, Vietnam. Photography was used in an observational study conducted among five separate retail market chains all located in this city. In which ways are the applications of the developed food safety labelling techniques among three separate retail food markets similar and dissimilar being accounted for? The results show that the packaging and labelling in Big C, Aeon Citimart, and Giant using the symbols of food safety build trust for their customers. The Big C indicates guidelines for VietGAP and green labelling. Aeon Citimart indicates the name of the good, expiration date and instructions for use as well as guidelines for the government factor (VietGAP) to the food safety practices in the Vietnamese food retail sector.

This study aims to assess the efficiency of Brazil, Russia, India, China, South Africa (BRICS) countries in achieving sustainable development by analyzing their ability to convert resources and technological innovations into sustainable outcomes.

Using data envelopment analysis (DEA), the study evaluates the economic, environmental and social efficiency of BRICS countries over the period 2010–2018. It ranks these countries based on their sustainable development performance and compares them to the period 2000–2007.

The study reveals varied efficiency levels among BRICS countries. Russia and South Africa lead in certain sustainable development aspects. South Africa excels in environmental sustainability, whereas Brazil is efficient in resource utilization for sustainable growth. China and India, despite economic growth, face challenges such as pollution and lower quality of life.

The study’s findings are constrained by the DEA methodology and the selection of variables. It highlights the need for more nuanced research incorporating recent global events such as the COVID-19 pandemic and geopolitical shifts.

Insights from this study can inform targeted and effective sustainability strategies in BRICS nations, focusing on areas such as industrial quality improvement, employment conditions and environmental policies.

The study underscores the importance of balancing economic growth with social and environmental considerations, highlighting the need for policies addressing inequality, poverty and environmental degradation.

This research provides a unique comparative analysis of BRICS countries’ sustainable development efficiency, challenging conventional perceptions and offering a new perspective on their progress.

Since the end of 2016, “fake news” has had a clear meaning in the USA. After years of scholarship attempting to define “fake news” and where it fits among the larger schema of media hoaxing and deception, popular culture and even academic studies converged following the 2016 US presidential election to define “fake news” in drastically new ways. The paper aims to discuss these issues.

In light of the recent elections in the USA, many fear “fake news” that have gradually become a powerful and sinister force, both in the news media environment as well as in the fair and free elections. The scenario draws into questions how the general public interacts with such outlets, and to what extent and in which ways individual responsibility should govern the interactions with social media.

Fake news is a growing threat to democratic elections in the USA and other democracies by relentless targeting of hyper-partisan views, which play to the fears and prejudices of people, in order to influence their voting plans and their behavior.

Essentially, “fake news” is changing and even distorting how political campaigns are run, ultimately calling into question legitimacy of elections, elected officials and governments. Scholarship has increasingly confirmed social media as an enabler of “fake news,” and continues to project its potentially negative impact on democracy, furthering the already existing practices of partisan selective exposure, as well as heightening the need for individual responsibility.

This paper examines the relationship between transport connectivity and regional economic development in China. It develops measurements appropriate for transport connectivity based on a set of evaluation models. This model is used to analyze the logistic connectivity of China’s 31 provinces by focusing on 11 variables, including some new factors (Density of road network, Density of railway network, Number of Internet Users) not used in previous studies, over the 13-year period from 2002 to 2014. Using panel data regression analysis, the empirical results show a statistically significant and positive impact of transport connectivity (factors like Density of road network, Density of railway network and Number of Internet Users) on economic development in China. In particular, the Number of internet users is a key factor reflecting information connectivity in all the variables. Comparative analysis regarding economic development is conducted to benchmark between coastal provinces and interior provinces. Like most previous research, this study yields the same finding of higher impact of transport connectivity on economic development in eastern provinces than in western provinces. This study suggests that decentralized decision-making will be significantly more efficient for analyzing regional infrastructure development. It also shows that the influence of transport connectivity on economic development is dependent on a certain developmental stage. This suggests that an economic region should adopt different development strategies for transport connectivity during different stages of development.

Based on an exploratory case-based approach, the purpose of this paper is to open the KM black box and examine the relationships that link knowledge management (KM) inputs (i.e. knowledge resources and KM practices) via knowledge processes to KM performance. This paper aims to identify the underlying mechanisms and explain how KM performance is enabled.

This in-depth case study conducted at a medium-sized consultancy in the supply chain management industry empirically examines knowledge flows to uncover the relationships between KM inputs, knowledge processes and KM performance. We adopt the viable system model (VSM) as a theoretical lens to identify KM mechanisms.

By identifying six KM mechanisms, we contribute to the theoretical understanding of how KM inputs are interconnected and lead to KM performance via knowledge processes.

Based on the insights gained, we provide propositions that organizations should consider in designing viable KM. Our findings help organizations in understanding their KM with the help of knowledge flow analysis and identifying how critical KM elements are interconnected.