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1 – 10 of 465Aditya Korekallu Srinivasa, K.V. Praveen, Subash Surendran Padmaja, M.L. Nithyashree and Girish K. Jha
This paper examines whether farmers' knowledge of the minimum support prices (MSPs) affects farm-gate prices. MSP is the minimum guaranteed price for agricultural commodities…
Abstract
Purpose
This paper examines whether farmers' knowledge of the minimum support prices (MSPs) affects farm-gate prices. MSP is the minimum guaranteed price for agricultural commodities announced by the Government of India for 24 commodities. Most farmers in India prefer to sell their produce at the farm-gate due to a small marketable surplus and hence do not directly benefit from MSP. The authors test the common argument in the political discourse that if farmers have knowledge of MSP, then they can bargain with traders during the farm-gate transaction and demand a better price close to MSP.
Design/methodology/approach
The authors use matching methods to examine the impact of knowledge of MSP on farm-gate prices.
Findings
Using nationally representative data, the authors show that there is no empirical evidence that the knowledge of MSP of the crops leads to higher bargaining power and better farm-gate prices.
Practical implications
Price information (MSP in this case) alone cannot improve the bargaining power of farmers and result in a better price realization. As a safety net, MSP fails in the absence of procurement of products by the government. This also raises the question of the equitability of the price support system in India and calls for a rethink of the MSP policy.
Originality/value
This study is the first of its kind to examine the anchoring effect of knowledge of MSP on farm-gate prices using a nationally representative dataset.
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Key to transnational higher education (HE) cooperation is building trust to allow for seamless recognition of studies. Building on the Tuning Educational Structures initiative…
Abstract
Purpose
Key to transnational higher education (HE) cooperation is building trust to allow for seamless recognition of studies. Building on the Tuning Educational Structures initiative (2001) and lessons learnt from the Organisation for Economic Cooperation and Development (OECD)-Assessment of Learning Outcomes in Higher Education (AHELO) feasibility study, this paper offers a sophisticated approach developed by the European Union (EU)-co-financed project Measuring and Comparing Achievements of Learning Outcomes in Europe (CALOHEE). These evidence the quality and relevance of learning by applying transparent and reliable indicators at the overarching and disciplinary levels. The model results allow for transnational diagnostic assessments to identify the strength and weaknesses of degree programmes.
Design/methodology/approach
The materials presented have been developed from 2016 to 2023, applying a bottom-up approach involving approximately 150 academics from 20+ European countries, reflecting the full spectrum of academic fields. Based on intensive face-to-face debate and consultation of stakeholders and anchored in academic literature and wide experience.
Findings
As a result, general (overarching) state-of-the-art reference frameworks have been prepared for the associated degree, bachelor, master and doctorate, as well as aligned qualifications reference frameworks and more detailed learning outcomes/assessment frameworks for 11 subject areas, offering a sound basis for quality assurance. As a follow-up, actual assessment formats for five academic fields have been developed to allow for measuring the actual level of learning at the institutional level from a comparative perspective.
Originality/value
Frameworks as well as assessment models and items are highly innovative, content-wise as in the strategy of development, involving renown academics finding common ground. Its value is not limited to Europe but has global significance. The model developed, is also relevant for micro-credentials in defining levels of mastery.
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Elif Ozturk, Hande Bahar Turker and V. Aslihan Nasir
Collaborating with consumers during new product development can provide companies with significant benefits and competitive advantages. Although several studies have been…
Abstract
Purpose
Collaborating with consumers during new product development can provide companies with significant benefits and competitive advantages. Although several studies have been conducted on the design of co-innovation platforms, there is still a need for a more comprehensive understanding of the co-innovation phenomenon. To address this gap, this research aims to identify the critical success factors of co-innovation platforms and provide an extensive analysis of the variables that determine their effectiveness.
Design/methodology/approach
This study presents a systematic literature review of co-innovation platforms based on an analysis of 89 articles published in 50 scholarly journals in the disciplines of information systems, marketing and business, covering the years from 2006 to 2022.
Findings
The review synthesizes the current state of scientific knowledge and groups prior studies thematically as critical success factors of co-innovation platforms. As a result, eight success factors have been identified in terms of quantity and quality of contributions. These factors include product involvement, perceived fairness, sense of community, interactive environment, employee involvement, participant diversity, assessment structure and task design.
Originality/value
The study consolidates existing research about the critical success of co-innovation platforms. It also provides a research framework that incorporates a diverse set of variables that can be used to assess co-innovation performance in future studies.
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Cecilia Albert and Maria A. Davia
This paper addresses the relevance of job search methods and strategies in determining vertical mismatch and the risk of underusing skills or knowledge in first jobs amongst…
Abstract
Purpose
This paper addresses the relevance of job search methods and strategies in determining vertical mismatch and the risk of underusing skills or knowledge in first jobs amongst graduates from bachelor's and master's programmes in Spain. Support from universities (via internships and career services) is compared to support from public institutions and informal strategies.
Design/methodology/approach
The authors use the 2019 University Graduate Job Placement Survey. The dependent variables are estimated with a bivariate probit model with sample selection on a subsample of graduates who were not working at graduation.
Findings
Internships and university career employment offices significantly improve the quality of first job matches. Job banks and public examinations also contribute to finding well-matched first positions, while for public employment services, results are mixed. When the job search is not supported by institutions, graduates generally do worse finding their first jobs, particularly when temporary employment agencies are involved. There are also large differences in mismatch risks across fields of study.
Practical implications
If more graduates found their first jobs through internships and university job placement services, educational mismatch rates would decrease substantially. Further collaboration between universities and employers for the provision of high-quality internships may foster their conversion into regular, well-matched jobs. Industrial policies addressed to knowledge-based economic activities would enhance the creation of highly skilled positions. Further orientation towards STEM degrees is required to improve imbalances between supply and demand for graduate labour in Spain.
Originality/value
Evidence about education mismatch among master's degree graduates is very scarce. This paper compares them to bachelor's degree graduates. It addresses two complementary types of education mismatch and takes into account potential self-selection into post-graduation job search.
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Sudhaman Parthasarathy and S.T. Padmapriya
Algorithm bias refers to repetitive computer program errors that give some users more weight than others. The aim of this article is to provide a deeper insight of algorithm bias…
Abstract
Purpose
Algorithm bias refers to repetitive computer program errors that give some users more weight than others. The aim of this article is to provide a deeper insight of algorithm bias in AI-enabled ERP software customization. Although algorithmic bias in machine learning models has uneven, unfair and unjust impacts, research on it is mostly anecdotal and scattered.
Design/methodology/approach
As guided by the previous research (Akter et al., 2022), this study presents the possible design bias (model, data and method) one may experience with enterprise resource planning (ERP) software customization algorithm. This study then presents the artificial intelligence (AI) version of ERP customization algorithm using k-nearest neighbours algorithm.
Findings
This study illustrates the possible bias when the prioritized requirements customization estimation (PRCE) algorithm available in the ERP literature is executed without any AI. Then, the authors present their newly developed AI version of the PRCE algorithm that uses ML techniques. The authors then discuss its adjoining algorithmic bias with an illustration. Further, the authors also draw a roadmap for managing algorithmic bias during ERP customization in practice.
Originality/value
To the best of the authors’ knowledge, no prior research has attempted to understand the algorithmic bias that occurs during the execution of the ERP customization algorithm (with or without AI).
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Science policy and practice for open access (OA) books is a rapidly evolving area in the scholarly domain. However, there is much that remains unknown, including how many OA books…
Abstract
Purpose
Science policy and practice for open access (OA) books is a rapidly evolving area in the scholarly domain. However, there is much that remains unknown, including how many OA books there are and to what degree they are included in preservation coverage. The purpose of this study is to contribute towards filling this knowledge gap in order to advance both research and practice in the domain of OA books.
Design/methodology/approach
This study utilized open bibliometric data sources to aggregate a harmonized dataset of metadata records for OA books (data sources: the Directory of Open Access Books, OpenAIRE, OpenAlex, Scielo Books, The Lens, and WorldCat). This dataset was then cross-matched based on unique identifiers and book titles to openly available content listings of trusted preservation services (data sources: Cariniana Network, CLOCKSS, Global LOCKSS Network, and Portico). The web domains of the OA books were determined by querying the web addresses or digital object identifiers provided in the metadata of the bibliometric database entries.
Findings
In total, 396,995 unique records were identified from the OA book bibliometric sources, of which 19% were found to be included in at least one of the preservation services. The results suggest reason for concern for the long tail of OA books distributed at thousands of different web domains as these include volatile cloud storage or sometimes no longer contained the files at all.
Research limitations/implications
Data quality issues, varying definitions of OA across services and inconsistent implementation of unique identifiers were discovered as key challenges. The study includes recommendations for publishers, libraries, data providers and preservation services for improving monitoring and practices for OA book preservation.
Originality/value
This study provides methodological and empirical findings for advancing the practices of OA book publishing, preservation and research.
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Jiayuan Zhao, Hong Huo, Sheng Wei, Chunjia Han, Mu Yang, Brij B. Gupta and Varsha Arya
The study employs two independent experimental studies to collect data. It focuses on the matching effect between advertising appeals and product types. The Elaboration Likelihood…
Abstract
Purpose
The study employs two independent experimental studies to collect data. It focuses on the matching effect between advertising appeals and product types. The Elaboration Likelihood Model serves as the theoretical framework for understanding the cognitive processing involved in consumers' responses to these advertising appeals and product combinations.
Design/methodology/approach
This paper aims to investigate the impact of advertising appeals on consumers' intentions to purchase organic food. We explored the interaction between advertising appeals (egoistic vs altruistic) and product types (virtue vs vice) and purchase intention. The goal is to provide insights that can enhance the advertising effectiveness of organic food manufacturers and retailers.
Findings
The analysis reveals significant effects on consumers' purchase intentions based on the matching of advertising appeals with product types. Specifically, when egoistic appeals align with virtuous products, there is an improvement in consumers' purchase intentions. When altruistic appeals match vice products, a positive impact on purchase intention is observed. The results suggest that the matching of advertising appeals with product types enhances processing fluency, contributing to increased purchase intention.
Originality/value
This research contributes to the field by providing nuanced insights into the interplay between advertising appeals and product types within the context of organic food. The findings highlight the importance of considering the synergy between egoistic appeals and virtuous products, as well as altruistic appeals and vice products. This understanding can be strategically employed by organic food manufacturers and retailers to optimize their advertising strategies, thereby improving their overall effectiveness in influencing consumers' purchase intentions.
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Rafal Kusa, Marcin Suder, Joanna Duda, Wojciech Czakon and David Juárez-Varón
This study investigates the impact of entrepreneurial orientation (EO) and knowledge management (KM) on firm performance (PERF), as well as the mediating role of KM in the EO–PERF…
Abstract
Purpose
This study investigates the impact of entrepreneurial orientation (EO) and knowledge management (KM) on firm performance (PERF), as well as the mediating role of KM in the EO–PERF (EO-PERF relationship). In particular, this study aims to explain the impact of KM on the relationship between the EO dimensions and PERF; dimensions are risk-taking (RT), innovativeness (IN) and proactiveness (PR).
Design/methodology/approach
This study uses structural equation modelling and fuzzy-set qualitative comparative analysis (fsQCA) methodologies to explore target relationships. The sample consists of 150 small furniture manufacturers operating in Poland (out of 1,480 in the population).
Findings
The study findings show that KM partially mediates the IN–PERF relationship. Furthermore, fsQCA reveals that KM accompanied by IN is a core condition that leads to PERF. Moreover, the absence of KM (accompanied by the absence of RT and IN) leads to the absence of PERF. In addition, the results show that all the variables examined (RT, IN, PR and KM) positively impact PERF.
Originality/value
This study explores the role of KM in the context of EO and its impact on PERF in the low-tech industry. The study uses simultaneously two methodologies that represent different approaches in the search for the expected relationships. The findings reveal that KM mediates the EO-PERF relationship.
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Gustavo Hermínio Salati Marcondes de Moraes, Bruno Fischer, Sergio Salles-Filho, Dirk Meissner and Marina Dabic
Knowledge-intensive entrepreneurial firms (KIE) strongly rely on scientific and strategic research and development (R&D) capabilities to achieve higher performance levels. Hence…
Abstract
Purpose
Knowledge-intensive entrepreneurial firms (KIE) strongly rely on scientific and strategic research and development (R&D) capabilities to achieve higher performance levels. Hence, the purpose of this paper is to disentangle the effects of scientific capabilities and strategic R&D on KIE performance; and how the constituent elements of these dimensions can be configured to generate conditions for high performance.
Design/methodology/approach
The authors’ empirical setting involves companies that submitted projects to the Innovative Research in Small Businesses (PIPE) program in Brazil. The authors then run partial least square structural equation modeling to verify how scientific and strategic R&D capabilities influence the performance construct. Second, the authors apply fuzzy-set qualitative comparative analysis to identify configurations that are equifinal in terms of generating superior performance.
Findings
Findings indicate a strong association between scientific capabilities and KIE performance. The configurational approach outlines the existence of multiple paths to success, but human capital stands as a core condition throughout estimations.
Practical implications
The authors’ assessment has implications for how KIE firms are managed according to their organizational profiles and trajectories. Also, it advances the authors’ comprehension on how entrepreneurship policies can better target these distinct profiles.
Originality/value
The authors’ analysis provides new evidence on the inherent complexity behind the generation of high performance in KIE when addressing their portfolios of knowledge-related capabilities. More than that, the authors were able to identify the existence of heterogeneous profiles that can equally lead to higher levels of performance.
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Melody Barlage, Arjan van den Born and Arjen van Witteloostuijn
More and more workers in Western economies are operating as freelancers in the so-called “gig economy”, moving from one project – or gig – to the next. A lively debate revolves…
Abstract
More and more workers in Western economies are operating as freelancers in the so-called “gig economy”, moving from one project – or gig – to the next. A lively debate revolves around the question as to whether this new employment relationship is actually good for innovation in the 21 st century economy. Proponents argue that in this gig process valuable knowledge is created and transferred from one organization to the next via freelancers through their sequence of temporary gigs or projects. Antagonists reason that freelancers are only hired as one-trick ponies on a transactional basis, where knowledge is neither created nor shared. In this study, we focus on the characteristics of gigs. Which project characteristics lead to increased engagement of freelancers, and hence to knowledge-sharing behavior? Our study suggests that the gig economy can indeed lead to increased knowledge sharing by and engagement of freelance workers, provided that organizations and freelancers structure and shape gigs in such a way that they: (1) not only suit the task requirements at hand and (2) fit with the acquired skills of the freelancer, but that these gigs also (3) leave ample of room for the freelancer’s individual growth and development of new skills. This suggests that innovative organizations will need to shape gigs in such a way that freelancers are not only hired for their expertise, but rather that gigs also provide a learning opportunity for freelancers.
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