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1 – 9 of 9Kasun Gomis, Mandeep Saini, Mohammed Arif and Chaminda Pathirage
Lack of appropriate student support and drawbacks in academic progression signify the importance of enhancing assessment and feedback in higher education (HE). Although assessment…
Abstract
Purpose
Lack of appropriate student support and drawbacks in academic progression signify the importance of enhancing assessment and feedback in higher education (HE). Although assessment and feedback are significant in HE, minimal empirical research holistically explores the best practices. This study aims to address the niche and develop a decisive guideline for enhancing assessment setting and feedback provision within HE curricula.
Design/methodology/approach
A systematic approach was taken to obtain data for the study: a literature review underpinning the thematic content analysis of study documents, followed by semi-structured interviews. Document analysis contained mid-module reviews/student feedback; rubrics used in assessment; and formative/summative feedback provided for the graded work. Documental analysis informed the key attributes of the semi-structured interview. Interpretive structural modelling (ISM) analysis identified the influence and reliance of each driver.
Findings
This study revealed 15 drivers – 4 fundamental, 6 significant and 5 important – for enhancing assessment and feedback. The level partitioning from the ISM analysis established that all assessment and feedback needs to be underpinned by the university policy and fed into the assessment regime and marking scheme. This study identified that National Student Survey results were significantly improved due to implementing said drivers compared with the national and sector benchmarks.
Practical implications
The developed drivers enable the best practices in assessment setting and feedback provision. The level partition diagram can be used as a decisive guideline or a provisional framework in assessment and feedback provision for quality assurance in HE.
Originality/value
This study is one of, if not the only, to develop a guideline for signposting drivers and their influence and reliance to enhance assessment and feedback in a holistic HE setting. The developed drivers and the level partition diagram bring novelty and add to the current body of knowledge.
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Ching Yin Ip and Chaoyun Liang
The present study surveyed consumers in Taiwan and Japan to analyse the influence of marketing mix on purchase intention and the willingness to pay for Taiwanese pork and to…
Abstract
Purpose
The present study surveyed consumers in Taiwan and Japan to analyse the influence of marketing mix on purchase intention and the willingness to pay for Taiwanese pork and to establish a marketing-oriented model of consumer behaviour.
Design/methodology/approach
A total of 1,134 valid Internet surveys were collected, which included 526 Taiwanese respondents and 608 Japanese respondents.
Findings
An analysis of the results indicated that product quality constitutes the foundation of marketing strategies and significantly affects purchase intention and willingness to pay through physical evidence, promotional activities, place and price. Both physical evidence and product strongly affect the purchase intention of Taiwanese consumers, followed by price, whereas price and physical evidence significantly affect willingness to pay. For Japanese consumers, price, product and promotion strongly affect purchase intention, but place and physical evidence exert negative effects; by contrast, price and promotion significantly affect willingness to pay.
Originality/value
The results determined that a modified marketing mix should be applied for agricultural products. In the domestic market, marketing should promote the modernisation and scale of pork farms and possibly the brand value or market rarity. In international markets, particularly those of neighbouring countries, marketing should focus on the promotion of Taiwanese pork as a high-quality, reasonably-priced product with transparent product information and convenient purchase channels. This study contributes to the application of marketing theory to the market for staple foods by incorporating considerations for domestic and international markets.
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Cyrus A. Ramezani and James J. Ahern
As digital technologies expand access to new forms of legalized gambling, including sports betting and online gaming, it is important to assess the impact of macroeconomic and…
Abstract
Purpose
As digital technologies expand access to new forms of legalized gambling, including sports betting and online gaming, it is important to assess the impact of macroeconomic and equity market outcomes on fund flows into gambling. The authors’ findings will be of interest to policymakers and the gambling industry, as various forms of gambling, including day trading, gain broad public acceptance.
Design/methodology/approach
The authors examine the impact of macroeconomic forces, business cycles, and financial market wealth on gambling. The authors propose a nonlinear model linking aggregate gambling expenditures to macroeconomic, stock market, and gambling industry variables. The authors estimate the proposed model using nonlinear estimation procedures.
Findings
The authors find that price of wagering, incomes, and supply of gambling opportunities are the primary determinants of wagering demand. Aggregate wagering is negatively impacted by realized stock returns and market volatility, but rises during recessions.
Originality/value
To the best of the authors’ knowledge, the questions posed and addressed in this manuscript have not been addressed in prior literature.
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Rinu Sathyan, Parthiban Palanisamy, Suresh G. and Navin M.
The automotive industry appears to overcome much of its obstacles, despite the constant struggle facing COVID-19. The pandemic has resulted in significant improvements in the…
Abstract
Purpose
The automotive industry appears to overcome much of its obstacles, despite the constant struggle facing COVID-19. The pandemic has resulted in significant improvements in the habits and conduct of consumers. There is an increased preference for personal mobility. In this dynamic environment with unexpected changes and high market rivalry, automotive supply chains focus more on executing responsive strategies with minimum costs. This paper aims to identify and model the drivers to the responsiveness of automotive supply chain.
Design/methodology/approach
Seventeen drivers for supply chain responsiveness have been identified from the extensive literature, expert interview. An integrated methodology of fuzzy decision-making trial and evaluation laboratory–interpretive structural modelling (DEMATEL–ISM) is developed to establish the interrelationship between the drivers. The cause–effect relationship between the drivers was obtained through fuzzy DEMATEL technique, and a hierarchical structure of the drivers was developed using the ISM technique.
Findings
The result of the integrated methodology revealed that strategic decision-making of management, accurate forecasting of demand, advanced manufacturing system in the organisation and data integration tools are the critical drivers.
Research limitations/implications
This study has conceptual and analytical limitations. In this study, a limited number of drivers are examined for supply chain responsiveness. Further research may examine the role of other key performance indicators in the broad field of responsiveness in the automotive supply chain or other industry sectors. Future study can uncover the interrelationships and relative relevance of indicators using advanced multi-criteria decision-making methodologies.
Originality/value
The authors proposed an integrated methodology that will be benefitted to the supply chain practitioners and automotive manufacturers to develop management strategies to improve responsiveness. This study further helps to compare the responsiveness of the supply chain between various automotive manufacturers.
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Yi-Hsin Lin, Ruixue Zheng, Fan Wu, Ningshuang Zeng, Jiajia Li and Xingyu Tao
This study aimed to improve the financing credit evaluation for small and medium-sized real estate enterprises (SMREEs). A financing credit evaluation model was proposed, and a…
Abstract
Purpose
This study aimed to improve the financing credit evaluation for small and medium-sized real estate enterprises (SMREEs). A financing credit evaluation model was proposed, and a blockchain-driven financing credit evaluation framework was designed to improve the transparency, credibility and applicability of the financing credit evaluation process.
Design/methodology/approach
The design science research methodology was adopted to identify the main steps in constructing the financing credit model and blockchain-driven framework. The fuzzy analytic hierarchy process (FAHP)–entropy weighting method (EWM)–set pair analysis (SPA) method was used to design a financing credit evaluation model. Moreover, the proposed framework was validated using data acquired from actual cases.
Findings
The results indicate that: (1) the proposed blockchain-driven financing credit evaluation framework can effectively realize a transparent evaluation process compared to the traditional financing credit evaluation system. (2) The proposed model has high effectiveness and can achieve efficient credit ranking, reflect SMREEs' credit status and help improve credit rating.
Originality/value
This study proposes a financing credit evaluation model of SMREEs based on the FAHP–EWM–SPA method. All credit rating data and evaluation process data are immediately stored in the proposed blockchain framework, and the immutable and traceable nature of blockchain enhances trust between nodes, improving the reliability of the financing credit evaluation process and results. In addition, this study partially fulfills the lack of investigations on blockchain adoption for SMREEs' financing credit.
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Despite the escalating significance and intricate nature of supply chains, there has been limited scholarly attention devoted to exploring the cognitive processes that underlie…
Abstract
Purpose
Despite the escalating significance and intricate nature of supply chains, there has been limited scholarly attention devoted to exploring the cognitive processes that underlie supply chain management. Drawing on cognitive-behavioral theory, the authors propose a moderated-mediation model to investigate how paradoxical leadership impacts manufacturing supply chain resilience.
Design/methodology/approach
By conducting a two-wave study encompassing 164 supply chain managers from Chinese manufacturing firms, the authors employ partial least squares structural equation modeling (PLS-SEM) to empirically examine and validate the proposed hypotheses.
Findings
The findings indicate that managers' paradoxical cognition significantly affects supply chain resilience, with supply chain ambidexterity acting as a mediating mechanism. Surprisingly, the study findings suggest that big data analytics negatively moderate the effect of paradoxical cognition on supply chain ambidexterity and supply chain resilience, while positively moderating the effect of supply chain ambidexterity on supply chain resilience.
Research limitations/implications
These findings shed light on the importance of considering cognitive factors and the potential role of big data analytics in enhancing manufacturing supply chain resilience, which enriches the study of behavioral operations.
Practical implications
The results offer managerial guidance for leaders to use paradoxical cognition frames and big data analytics properly, offering theoretical insight for future research in manufacturing supply chain resilience.
Originality/value
This is the first empirical research examining the impact of paradoxical leadership on supply chain resilience by considering the role of big data analytics and supply chain ambidexterity.
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This study aimed to examine the antecedents, correlates, and consequences of burnout among higher education faculty in Saudi Arabia using the theoretical framework of the job…
Abstract
Purpose
This study aimed to examine the antecedents, correlates, and consequences of burnout among higher education faculty in Saudi Arabia using the theoretical framework of the job demands-resources model.
Design/methodology/approach
Using a quantitative research design, a cross-sectional survey was employed to collect data from faculty members across multiple Saudi universities. The constructs were measured using validated scales, and data analysis included exploratory factor analysis, Pearson correlation analysis, factorial ANOVA, and multiple regression.
Findings
The study identified moderate levels of burnout, confirming a significant positive relationship with role conflict and a negative relationship with internal locus of control. Burnout significantly contributed to depression, insomnia, and turnover intentions. However, no significant relationship was found between burnout and workplace conflict when controlling for other variables.
Research limitations/implications
The study's findings can inform policymakers and academic administrators about measures to alleviate faculty burnout, thus contributing to healthier academic work environments aligned with Saudi Arabia's Vision 2030 goals.
Originality/value
This research extends the job demands-resources model within the context of higher education institutions in Saudi Arabia, offering nuanced insights into burnout dynamics among university faculty in this region. Despite the model's robustness, the absence of a significant relationship between burnout and workplace conflict signals the need for a more intricate understanding of burnout's antecedents and consequences.
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Soumyananda Dinda and Poulomi Khasnobis
This paper examines the role of institution in the combating crime in India. This study also assesses institutions for controlling property crime in India in the post-reform era.
Abstract
Purpose
This paper examines the role of institution in the combating crime in India. This study also assesses institutions for controlling property crime in India in the post-reform era.
Design/methodology/approach
Crime and socio-economic data are taken from National Crime Record Bureau and the Reserve Bank of India, respectively. Twenty major Indian states are selected for the study purpose for the period of 1994–2019. Fixed effect panel data technique is used for analysis purpose.
Findings
Property crime rate declines with economic growth, while it increases with financial development. Findings of fiscal policy instruments are different. Own tax is positively associated with property crime in India, while non-tax fiscal instruments such as fine, penalty, and so on, are inversely related to it. Property crime rate is inversely related to institutional factors like charge sheet and conviction rate.
Research limitations/implications
Further research is needed for other crimes in India. State-level data are used here for analysis purpose; however, spatial or cluster analysis techniques might provide more insights for combating crimes in India.
Practical implications
This study suggests that economic growth and fiscal instrument along with institutional development are essential to control property crime in India.
Social implications
Government should take steps to improve the law-and-order system to control property crime across states.
Originality/value
Impact of non-tax fiscal instrument reduces property crime while that of own tax is increases it in India. These findings are unique and added certain insight in the study. Institutional roles are captured its performances like charge sheet and convict rate, which are significantly reduce property crime in Indian states. Least square dummy variable model is applied to capture individual state effects.
Peer review
The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-01-2023-0063
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Chin Ann Chong, Lee Peng Ng and I-Chi Chen
This study evaluates the moderating role of work-based social supports (i.e. supervisor support and co-worker support) in the relationship between job insecurity and job burnout…
Abstract
Purpose
This study evaluates the moderating role of work-based social supports (i.e. supervisor support and co-worker support) in the relationship between job insecurity and job burnout among hospitality employees in Malaysia. Besides, the direct effect between job insecurity and job burnout is examined.
Design/methodology/approach
The cross-sectional data of this study were based on a total of 220 self-administered questionnaires that have been completed by hospitality employees from three different states in Malaysia. Respondents were recruited based on a snowball sampling approach. The data were collected during the COVID-19 pandemic, which was from October 2020 to January 2021.
Findings
Partial least square-structural equation modeling (PLS-SEM) was performed via SmartPLS software. The finding confirmed that job insecurity significantly intensifies employees' job burnout. Supervisor support and co-worker support were found to moderate the link between job insecurity and burnout. As anticipated, the relationship between job insecurity and job burnout increased when supervisor support is low. But high co-worker support was found to strengthen the impact of job insecurity on job burnout instead of the reverse.
Originality/value
This study supplements the existing literature by clarifying which sources of work-based social support (i.e. co-worker support or supervisor) is more salient in alleviating the adverse impact of job insecurity on job burnout during the COVID-19 pandemic among hospitality employees in Malaysia.
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