Habib ur Rehman Makhdoom, Cai Li and Shoaib Asim
This paper aims to develop an original framework of innovation and to explore the complexity of association between individual and collective (team-based) entrepreneurship, and…
Abstract
Purpose
This paper aims to develop an original framework of innovation and to explore the complexity of association between individual and collective (team-based) entrepreneurship, and their simultaneous impacts on innovation in context of small and medium enterprises (SMEs).
Design/methodology/approach
An integral theoretical framework is developed to encourage innovation and the hypothetical relations are tested with the help of structural equation modeling (SEM) through AMOS. Data were gathered through survey technique and the questioners were distributed through email among 700 entrepreneurs from SMEs operating in five major industrial cities of Punjab province Pakistan.
Findings
The results of SEM analyses confirm that both the individual entrepreneur and the collective efforts of all the business members contribute to innovation in SMEs. Entrepreneur’s personality traits have a direct positive impact on innovation while the centralized decision-making by entrepreneur is not associated with innovation. Centralized decision-making is found to be negatively associated with communication and have insignificant positive association with collaboration. Factors associated with the team-based entrepreneurship like communication and collaboration among members of the SME’s contribute to the entrepreneurial orientation and collective entrepreneurship. Entrepreneurial orientation and collective entrepreneurship have direct positive impact on innovation in SMEs.
Practical implications
It is imperative for SMEs to encourage decentralized organizational culture and participative leadership to bring innovation into their products and processes and further to improve their competitive advantage.
Originality/value
To the best of author knowledge, present study is a first attempt that explores the complex association between individual and team-based entrepreneurship and further, empirically investigate the simultaneous impacts of these variables on innovation in context of SMEs.
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Shweta V. Matey, Dadarao N. Raut, Rajesh B. Pansare and Ravi Kant
Blockchain technology (BCT) can play a vital role in manufacturing industries by providing visibility and real-time transparency. With BCT adoption, manufacturers can achieve…
Abstract
Purpose
Blockchain technology (BCT) can play a vital role in manufacturing industries by providing visibility and real-time transparency. With BCT adoption, manufacturers can achieve higher productivity, better quality, flexibility and cost-effectiveness. The current study aims to prioritize the performance metrics and ranking of enablers that may influence the adoption of BCT in manufacturing industries through a hybrid framework.
Design/methodology/approach
Through an extensive literature review, 4 major criteria with 26 enablers were identified. Pythagorean fuzzy analytical hierarchy process (AHP) method was used to compute the weights of the enablers and the Pythagorean fuzzy combined compromise solution (Co-Co-So) method was used to prioritize the 17-performance metrics. Sensitivity analysis was then carried out to check the robustness of the developed framework.
Findings
According to the results, data security enablers were the most significant among the major criteria, followed by technology-oriented enablers, sustainability and human resources and quality-related enablers. Further, the ranking of performance metrics shows that data hacking complaints per year, data storage capacity and number of advanced technologies available for BCT are the top three important performance metrics. Framework robustness was confirmed by sensitivity analysis.
Practical implications
The developed framework will contribute to understanding and simplifying the BCT implementation process in manufacturing industries to a significant level. Practitioners and managers may use the developed framework to facilitate BCT adoption and evaluate the performance of the manufacturing system.
Originality/value
This study can be considered as the first attempt to the best of the author’s knowledge as no such hybrid framework combining enablers and performance indicators was developed earlier.
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Deepak Datta Nirmal, K. Nageswara Reddy and Sujeet Kumar Singh
The main purpose of this study is to provide a comprehensive review and critical insights of the application of fuzzy methods in modeling, assessing and understanding the various…
Abstract
Purpose
The main purpose of this study is to provide a comprehensive review and critical insights of the application of fuzzy methods in modeling, assessing and understanding the various aspects of green and sustainable supply chains (SSCs).
Design/methodology/approach
The present study conducts a systematic literature review (SLR) and bibliometric analysis of 252 research articles. This study employs various tools such as VOSviewer version 1.6.10, Publish or Perish, Mendeley and Excel that aid in descriptive analysis, bibliometric analysis and network visualization. These tools have been used for performing citation analysis, top authors' analysis, co-occurrence of keywords, cluster and content analysis.
Findings
The authors have divided the literature into seven application areas and discussed detailed insights. This study has observed that research in the social sustainability area, including various issues like health and safety, labor rights, discrimination, etc. is scarce. Integration of the Industry 4.0 technologies like blockchain, big data analytics, Internet of Things (IoT) with the sustainable and green supply chain (GSC) is a promising field for future research.
Originality/value
The authors' contribution primarily lies in providing the integrated framework which shows the changing trends in the use of fuzzy methods in the sustainability area classifying and consolidating green and sustainable supply chain management (SSCM) literature in seven major areas where fuzzy methods are predominantly applied. These areas have been obtained after the analysis of clusters and content analysis of the literature presenting key insights from the past and developing the conceptual framework for future research studies.
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Hamed Gheibdoust and Mehdi Jabbari Zideh
Nowadays, the electricity supply chain is significant for most societies, so it is necessary to use new technologies such as blockchain in the electricity industry. This study…
Abstract
Purpose
Nowadays, the electricity supply chain is significant for most societies, so it is necessary to use new technologies such as blockchain in the electricity industry. This study aims to identify and prioritize the factors influencing the adoption of blockchain technology in the electricity supply chain of the US.
Design/methodology/approach
In this study, after reviewing the research literature, the influential factors of blockchain adoption in the electricity industry are identified and the consensus of the experts is reached. Experts have a thorough understanding of blockchain technology and the US electricity industry. Data is collected using a Step-Wise Weight Assessment Ratio Analysis (SWARA) questionnaire from November 2022 to July 2023. Using the SWARA questionnaire, experts compared 16 influential subcriteria of blockchain adoption. Then, using the Fuzzy SWARA method, the following influential subcriteria of blockchain adaptation in the US electricity industry are evaluated and prioritized.
Findings
The results show that the most significant subcriterion among the 16 influential subcriteria for the adoption of blockchain technology in the electricity supply chain is reducing cost, whereas the collaborating with supply chain partners subcriterion is recognized as the least important subcriterion.
Originality/value
The present study helps managers improve their knowledge to apply blockchain technology and also have the best performance for applying blockchain technology in the electricity supply chain.
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Shakiba Narjabadi Fam and Ramona Massoud
Food safety is among the most important topics in the world. According to WHO guidelines, aflatoxins are one of the most hazardous food toxins. Therefore, their detection in food…
Abstract
Purpose
Food safety is among the most important topics in the world. According to WHO guidelines, aflatoxins are one of the most hazardous food toxins. Therefore, their detection in food products seems crucial due to health problems. The purpose of this paper is to discuss the different types of biosensors in aflatoxin determination.
Design/methodology/approach
Traditional detection methods are time consuming and expensive. As fast and accurate detection is important in monitoring food contaminants, alternative analytical methods would be essential. Biosensors are the intelligent design of sensitive sensors for precise detection of toxins in a short time. Various biosensors are being applied for aflatoxins detection in food products with many advantages over the traditional methods.
Findings
Biosensors are cost-effective, stable and have possessed high selectivity, specificity and accuracy in aflatoxins detection. Applying biosensors has been increased recently, so biosensing methods (optical, electrochemical, piezoelectrical, immunosensors, surface plasmon resonance and calorimetric) are discussed along with their advantages in this article.
Research limitations/implications
More efforts should be occurred to detect and decrease the aflatoxins by biosensors, and some traits like accuracy and selectivity would be the purpose of future projects. The combination of various techniques would also help in toxin detection issue in food products, so high efforts in this regard are also required for the upcoming years.
Originality/value
This article also reviews different types of biosensors simultaneously and explains their specificity for aflatoxin determination in different food products and also the future trends and requirements.
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Umakant L. Tupe, Sachin D. Babar, Sonali P. Kadam and Parikshit N. Mahalle
Internet of Things (IoT) is an up-and-coming conception that intends to link multiple devices with each other. The aim of this study is to provide a significant analysis of Green…
Abstract
Purpose
Internet of Things (IoT) is an up-and-coming conception that intends to link multiple devices with each other. The aim of this study is to provide a significant analysis of Green IoT. The IoT devices sense, gather and send out significant data from their ambiance. This exchange of huge data among billions of devices demands enormous energy. Green IoT visualizes the concept of minimizing the energy consumption of IoT devices and keeping the environment safe.
Design/methodology/approach
This paper attempts to analyze diverse techniques associated with energy-efficient protocols in green IoT pertaining to machine-to-machine (M2M) communication. Here, it reviews 73 research papers and states a significant analysis. Initially, the analysis focuses on different contributions related to green energy constraints, especially energy efficiency, and different hierarchical routing protocols. Moreover, the contributions of different optimization algorithms in different state-of-the-art works are also observed and reviewed. Later the performance measures computed in entire contributions along with the energy constraints are also checked to validate the effectiveness of entire contributions. As the number of contributions to energy-efficient protocols in IoT is low, the research gap will focus on the development of intelligent energy-efficient protocols to build up green IoT.
Findings
The analysis was mainly focused on the green energy constraints and the different robust protocols and also gives information on a few powerful optimization algorithms. The parameters considered by the previous research works for improving the performance were also analyzed in this paper to get an idea for future works. Finally, the paper gives some brief description of the research gaps and challenges for future consideration that helps during the development of an energy-efficient green IoT pertaining to M2M communication.
Originality/value
To the best of the authors’ knowledge, this is the first work that reviews 65 research papers and states the significant analysis of green IoT.
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Engaged employees assure organizational competitiveness and sustainability. The purpose of this study is to explore the relationship between job resources and employee turnover…
Abstract
Purpose
Engaged employees assure organizational competitiveness and sustainability. The purpose of this study is to explore the relationship between job resources and employee turnover intentions, with employee engagement as a mediating variable.
Design/methodology/approach
Data were collected from 934 employees of eight wholly-owned pharmaceutical industries. The proposed model and hypotheses were evaluated using structural equation modeling. Construct reliability and validity was established through confirmatory factor analysis.
Findings
Data supported the hypothesized relationship. The results show that job autonomy and employee engagement were significantly associated. Supervisory support and employee engagement were significantly associated. However, performance feedback and employee engagement were nonsignificantly associated. Employee engagement had a significant influence on employee turnover intentions. The results further show that employee engagement mediates the association between job resources and employee turnover intentions.
Research limitations/implications
The generalizability of the findings will be constrained due to the research’s pharmaceutical industry focus and cross-sectional data.
Practical implications
The study’s findings will serve as valuable pointers for stakeholders and decision-makers in the pharmacuetical industry to develop a proactive and well-articulated employee engagement intervention to ensure organizational effectiveness, innovativeness and competitiveness.
Originality/value
By empirically demonstrating that employee engagement mediates the nexus of job resources and employee turnover intentions, the study adds to the corpus of literature.