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1 – 10 of 446Koraljka Golub, Xu Tan, Ying-Hsang Liu and Jukka Tyrkkö
This exploratory study aims to help contribute to the understanding of online information search behaviour of PhD students from different humanities fields, with a focus on…
Abstract
Purpose
This exploratory study aims to help contribute to the understanding of online information search behaviour of PhD students from different humanities fields, with a focus on subject searching.
Design/methodology/approach
The methodology is based on a semi-structured interview within which the participants are asked to conduct both a controlled search task and a free search task. The sample comprises eight PhD students in several humanities disciplines at Linnaeus University, a medium-sized Swedish university from 2020.
Findings
Most humanities PhD students in the study have received training in information searching, but it has been too basic. Most rely on web search engines like Google and Google Scholar for publications' search, and university's discovery system for known-item searching. As these systems do not rely on controlled vocabularies, the participants often struggle with too many retrieved documents that are not relevant. Most only rarely or never use disciplinary bibliographic databases. The controlled search task has shown some benefits of using controlled vocabularies in the disciplinary databases, but incomplete synonym or concept coverage as well as user unfriendly search interface present hindrances.
Originality/value
The paper illuminates an often-forgotten but pervasive challenge of subject searching, especially for humanities researchers. It demonstrates difficulties and shows how most PhD students have missed finding an important resource in their research. It calls for the need to reconsider training in information searching and the need to make use of controlled vocabularies implemented in various search systems with usable search and browse user interfaces.
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Roberto Linzalone, Salvatore Ammirato and Alberto Michele Felicetti
Crowdfunding (CF) is a digital-financial innovation that, bypassing credit crisis, bank system rigidities and constraints of the capital market, is allowing new ventures and…
Abstract
Purpose
Crowdfunding (CF) is a digital-financial innovation that, bypassing credit crisis, bank system rigidities and constraints of the capital market, is allowing new ventures and established companies to get the needed funds to support innovations. After one decade of research, mainly focused on relations between variables and outcomes of the CF campaign, the literature shows methodological lacks about the study of its overall behavior. These reflect into a weak theoretical understanding and inconsistent managerial guidance, leading to a 27% success ratio of campaigns. To bridge this gap, this paper embraces a “complex system” perspective of the CF campaign, able to explore the system's behavior of a campaign over time, in light of its causal loop structure.
Design/methodology/approach
By adopting and following the document model building (DMB) methodology, a set of 26 variables and mutual causal relations modeled the system “Crowdfunding campaign” and a data set based on them and crafted to model the “Crowdfunding campaign” with a causal loop diagram. Finally, system archetypes have been used to link the causal loop structure with qualitative trends of CF's behavior (i.e. the raised capital over time).
Findings
The research brought to 26 variables making the system a “Crowdfunding campaign.” The variables influence each other, thus showing a set of feedback loops, whose structure determines the behavior of the CF campaign. The causal loop structure is traced back to three system archetypes, presiding the behavior in three stages of the campaign.
Originality/value
The value of this paper is both methodological and theoretical. First, the DMB methodology has been expanded and reinforced concerning previous applications; second, we carried out a causation analysis, unlike the common correlation analysis; further, we created a theoretical model of a “Crowdfunding Campaign” unlike the common empirical models built on CF platform's data.
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Usman Musa, Mastura Jaafar and Faraziera Mohd Raslim
This study attempts to examine the factors that influence user intention to adopt e-procurement in the Nigerian public sector.
Abstract
Purpose
This study attempts to examine the factors that influence user intention to adopt e-procurement in the Nigerian public sector.
Design/methodology/approach
A well-structured questionnaire was used to collect primary data from 278 procurement and information technology (IT) departments’ officials of key federal government ministries and agencies. The technology acceptance model (TAM) model was adopted and extended with security-related factors, namely perceived trust and perceived security. A partial least squares-structural equation modelling (PLS-SEM) approach was used to test and validate the model.
Findings
The results indicated that perceived usefulness is the best predictor of users’ intention to adopt e-procurement, followed by perceived security and perceived trust. In contrast, however, perceived ease of use was found to have a significant negative effect on the intention to adopt e-procurement.
Originality/value
This study is among the first in the Nigerian public sector context to evaluate users’ perceptions on e-procurement adoption with the use of a distinctive research model (TAM). The study's findings contribute to a better understanding of the factors influencing the adoption of e-procurement in the Nigerian public sector.
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Mahesh Babu Purushothaman and Kasun Moolika Gedara
This pragmatic research paper aims to unravel the smart vision-based method (SVBM), an AI program to correlate the computer vision (recorded and live videos using mobile and…
Abstract
Purpose
This pragmatic research paper aims to unravel the smart vision-based method (SVBM), an AI program to correlate the computer vision (recorded and live videos using mobile and embedded cameras) that aids in manual lifting human pose deduction, analysis and training in the construction sector.
Design/methodology/approach
Using a pragmatic approach combined with the literature review, this study discusses the SVBM. The research method includes a literature review followed by a pragmatic approach and lab validation of the acquired data. Adopting the practical approach, the authors of this article developed an SVBM, an AI program to correlate computer vision (recorded and live videos using mobile and embedded cameras).
Findings
Results show that SVBM observes the relevant events without additional attachments to the human body and compares them with the standard axis to identify abnormal postures using mobile and other cameras. Angles of critical nodal points are projected through human pose detection and calculating body part movement angles using a novel software program and mobile application. The SVBM demonstrates its ability to data capture and analysis in real-time and offline using videos recorded earlier and is validated for program coding and results repeatability.
Research limitations/implications
Literature review methodology limitations include not keeping in phase with the most updated field knowledge. This limitation is offset by choosing the range for literature review within the last two decades. This literature review may not have captured all published articles because the restriction of database access and search was based only on English. Also, the authors may have omitted fruitful articles hiding in a less popular journal. These limitations are acknowledged. The critical limitation is that the trust, privacy and psychological issues are not addressed in SVBM, which is recognised. However, the benefits of SVBM naturally offset this limitation to being adopted practically.
Practical implications
The theoretical and practical implications include customised and individualistic prediction and preventing most posture-related hazardous behaviours before a critical injury happens. The theoretical implications include mimicking the human pose and lab-based analysis without attaching sensors that naturally alter the working poses. SVBM would help researchers develop more accurate data and theoretical models close to actuals.
Social implications
By using SVBM, the possibility of early deduction and prevention of musculoskeletal disorders is high; the social implications include the benefits of being a healthier society and health concerned construction sector.
Originality/value
Human pose detection, especially joint angle calculation in a work environment, is crucial to early deduction of muscoloskeletal disorders. Conventional digital technology-based methods to detect pose flaws focus on location information from wearables and laboratory-controlled motion sensors. For the first time, this paper presents novel computer vision (recorded and live videos using mobile and embedded cameras) and digital image-related deep learning methods without attachment to the human body for manual handling pose deduction and analysis of angles, neckline and torso line in an actual construction work environment.
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This paper assesses the state and development of integrated thinking research in selected developed and developing economies by providing a “stock taking” of the literature…
Abstract
Purpose
This paper assesses the state and development of integrated thinking research in selected developed and developing economies by providing a “stock taking” of the literature included in the Scopus Database based on filtered criteria.
Design/methodology/approach
A search was performed on the Scopus Database and all sources containing “integrated thinking” in the title, abstract, or keywords were extracted. A total of 98 sources from 2011–2021 are analysed. These are coded with the support of a content analysis and a bibliometric analysis to determine research objectives and methods, affiliations, the locus of enquiry and epistemological perspectives.
Findings
There is a steady increase in attention devoted to integrated thinking research. The earliest studies were concerned primarily with the type of extra-financial information being included in an organisation's reports. This has given way to studies concerned with the operationalisation of integrated thinking. The current research has predominantly focussed on non-positivist epistemologies at the macro- and meso-levels with limited research undertaken at organisational levels.
Practical implications
Research on integrated thinking is particularly relevant in the context of developing economies where integrated thinking can be used as a means to value-creation, sustainable development and stakeholder inclusivity.
Social implications
This paper provides a useful reference for practitioners, academics and journal editors interested in the development of integrated thinking research.
Originality/value
This paper highlights the need for more active research on integrated thinking and reporting in developing economies because much of what has been published to date comes from developed nations. This paper provides an overview of the state of integrated thinking research and presents important areas for future research.
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Zaina Nakabuye, Jamiah Mayanja, Sarah Bimbona and Micheal Wassermann
The purpose of this paper is to investigate the relationships between technology orientations and export performance of small and medium-sized enterprises (SMEs).
Abstract
Purpose
The purpose of this paper is to investigate the relationships between technology orientations and export performance of small and medium-sized enterprises (SMEs).
Design/methodology/approach
A quantitative research design was adopted for this study. The paper formulates hypotheses from the literature review. These hypotheses are tested using structural equation modeling with data collected from 231 SMEs in Uganda. Data were analyzed using SPSS version 23 and AMOS.
Findings
The findings of this study showed technology orientation has a positive and significant relationship with the performance of Ugandan SMEs and that supply chain agility moderates technology orientation and export performance.
Research limitations/implications
The study discusses the findings, advances limitations and managerial implications. It also suggests future research avenues. It proposes some recommendations to help Ugandan SMEs to form flexible supply chains, use the latest technology and create strong relationship ties with their partners in the supply chain.
Practical implications
The study suggests that managers of Ugandan SMEs should use the latest technology in production, marketing, logistics and supply chain management which will enable them to respond quickly to customer tastes and preferences leading to higher levels of export performance.
Originality/value
This study contributes to the literature on strategic management showing the reliability of scales used and the confirmatory of the factor structure. This study shows that in strategic management technology, orientation is critical in increasing export performance. This study has extended the resource-based view (RBV) and dynamic capabilities theories.
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Assunta Di Vaio, Badar Latif, Nuwan Gunarathne, Manjul Gupta and Idiano D'Adamo
In this study, the authors examine artificial knowledge as a fundamental stream of knowledge management for sustainable and resilient business models in supply chain management…
Abstract
Purpose
In this study, the authors examine artificial knowledge as a fundamental stream of knowledge management for sustainable and resilient business models in supply chain management (SCM). The study aims to provide a comprehensive overview of artificial knowledge and digitalization as key enablers of the improvement of SCM accountability and sustainable performance towards the UN 2030 Agenda.
Design/methodology/approach
Using the SCOPUS database and Google Scholar, the authors analyzed 135 English-language publications from 1990 to 2022 to chart the pattern of knowledge production and dissemination in the literature. The data were collected, reviewed and peer-reviewed before conducting bibliometric analysis and a systematic literature review to support future research agenda.
Findings
The results highlight that artificial knowledge and digitalization are linked to the UN 2030 Agenda. The analysis further identifies the main issues in achieving sustainable and resilient SCM business models. Based on the results, the authors develop a conceptual framework for artificial knowledge and digitalization in SCM to increase accountability and sustainable performance, especially in times of sudden crises when business resilience is imperative.
Research limitations/implications
The study results add to the extant literature by examining artificial knowledge and digitalization from the resilience theory perspective. The authors suggest that different strategic perspectives significantly promote resilience for SCM digitization and sustainable development. Notably, fostering diverse peer exchange relationships can help stimulate peer knowledge and act as a palliative mechanism that builds digital knowledge to strengthen and drive future possibilities.
Practical implications
This research offers valuable guidance to supply chain practitioners, managers and policymakers in re-thinking, re-formulating and re-shaping organizational processes to meet the UN 2030 Agenda, mainly by introducing artificial knowledge in digital transformation training and education programs. In doing so, firms should focus not simply on digital transformation but also on cultural transformation to enhance SCM accountability and sustainable performance in resilient business models.
Originality/value
This study is, to the authors' best knowledge, among the first to conceptualize artificial knowledge and digitalization issues in SCM. It further integrates resilience theory with institutional theory, legitimacy theory and stakeholder theory as the theoretical foundations of artificial knowledge in SCM, based on firms' responsibility to fulfill the sustainable development goals under the UN's 2030 Agenda.
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Federico Brunetti, Angelo Bonfanti, Andrea Chiarini and Virginia Vannucci
This paper explores how digitalization affects the academic research publication process by taking into account the perspective of management scholars. It provides an overview of…
Abstract
Purpose
This paper explores how digitalization affects the academic research publication process by taking into account the perspective of management scholars. It provides an overview of the digital professional services dedicated to academic research, and investigates academics' awareness of, the impact on the publication process of, and scholars' expectations regarding digital services and software.
Design/methodology/approach
This explorative study adopted a qualitative approach by performing direct observations of websites regarding digital professional research services and in-depth interviews with national and international management scholars.
Findings
The multiple digital professional services dedicated to academic research enable authors to develop a scientific paper independently or with the support of professionals. The scholars' awareness regarding the digital services and software was limited, because of both the plethora of options on the market and the frequent use of the same digital tools over time. In impact terms, these tools enable scholars to improve research quality and to increase productivity. However, the negative effects led scholars to express different expectations about how they can be improved and what difficulties should be overcome to favor the publication process.
Practical implications
The results of this study provide suggestions both for scholars who engage in academic research and digital services and software providers.
Originality/value
To the best of the authors' knowledge, this is the first study to examine the ongoing development of digitalization in support of the research publication process from the perspective of academics.
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Kingstone Nyakurukwa and Yudhvir Seetharam
The authors’ goal is to provide an overview and historical context for the various alternatives to the efficient market hypothesis (EMH) that have emerged over time. The authors…
Abstract
Purpose
The authors’ goal is to provide an overview and historical context for the various alternatives to the efficient market hypothesis (EMH) that have emerged over time. The authors found eight current alternatives that have emerged to address the EMH's flaws. Each of the proposed alternatives improves some of the assumptions made by the EMH, such as investor homogeneity, the immediate incorporation of information into asset values and the inadequacy of rationality to explain asset prices.
Design/methodology/approach
To come up with the list of studies relevant to this review article, the authors used three databases, namely Scopus, Web of Science and Google Scholar. The first two were mostly used to get peer-reviewed articles while Google Scholar was used to extract articles that are still work in progress. The following words were used as the search queries; “efficient market hypothesis” and “alternatives to the efficient market hypothesis”.
Findings
The alternatives to the EMH presented in this article demonstrate that market efficiency is a dynamic concept that can be best understood with a multidisciplinary approach. To better comprehend how financial markets work, it is crucial to draw on concepts, theories and ideas from a variety of disciplines, including physics, economics, anthropology, sociology and others.
Originality/value
The authors comprehensively summarise the current state of the behavioural finance literature on alternatives to the EMH.
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Background: Commodity-driven deforestation is a major driver of forest loss worldwide, and globalisation has increased the disconnect between producer and consumer countries…
Abstract
Background: Commodity-driven deforestation is a major driver of forest loss worldwide, and globalisation has increased the disconnect between producer and consumer countries. Recent due-diligence legislation aiming to improve supply chain sustainability covers major forest-risk commodities. However, the evidence base for specific commodities included within policy needs assessing to ensure effective reduction of embedded deforestation.
Methods: We conducted a rapid evidence synthesis in October 2020 using three databases; Google Scholar, Web of Science, and Scopus, to assess the literature and identify commodities with the highest deforestation risk linked to UK imports. Inclusion criteria include publication in the past 10 years and studies that didn't link commodity consumption to impacts or to the UK were excluded. The development of a review protocol was used to minimise bias and critical appraisal of underlying data and methods in studies was conducted in order to assess the uncertainties around results.
Results: From a total of 318 results, 17 studies were included in the final synthesis. These studies used various methodologies and input data, yet there is broad alignment on commodities, confirming that those included in due diligence legislation have a high deforestation risk. Soy, palm oil, and beef were identified as critical, with their production being concentrated in just a few global locations. However, there are also emerging commodities that have a high deforestation risk but are not included in legislation, such as sugar and coffee. These commodities are much less extensively studied in the literature and may warrant further research and consideration.
Conclusion: Policy recommendations in the selected studies suggests further strengthening of the UK due diligence legislation is needed. In particular, the provision of incentives for uptake of policies and wider stakeholder engagement, as well as continual review of commodities included to ensure a reduction in the UK's overseas deforestation footprint.
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