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Open Access
Article
Publication date: 9 January 2023

Anni Rajala and Tuire Hautala-Kankaanpää

Small- and medium-sized enterprises (SMEs) often operate in environments marked by high levels of turbulence. Such firms adopt digital technologies and platforms that provide…

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Abstract

Purpose

Small- and medium-sized enterprises (SMEs) often operate in environments marked by high levels of turbulence. Such firms adopt digital technologies and platforms that provide access to external real-time information and establish digital connectivity between firms to remain competitive. This study aims to focus on SMEs’ downstream and upstream platform-based digital connectivity (PDC).

Design/methodology/approach

This study examines the effects of PDC on SMEs’ operational performance under conditions of environmental turbulence. The data was gathered from 192 SMEs operating in the manufacturing arena.

Findings

The results show that the adoption of PDC does not directly affect an SME’s operational performance. However, in highly turbulent environments, PDC can improve operational performance. The results indicate that the performance effects of PDC vary according to the level and type of environmental turbulence.

Research limitations/implications

This research offers insights into the relationship between PDC among SMEs and operational performance and encourages future research examining other possible conditional effects that could explain the contradictory results found in previous research.

Originality/value

This study contributes to the knowledge of supply-chain digitalization among SMEs and its performance effects in varying environmental conditions. Further, this study contributes to the prior research by focusing on the interorganizational aspects of digitalization in SMEs.

Details

Journal of Business & Industrial Marketing, vol. 38 no. 13
Type: Research Article
ISSN: 0885-8624

Keywords

Open Access
Article
Publication date: 26 January 2023

Gerard W. Toh, Wee Ling Koh, Jack Ho, Jackson Chia, Ad Maulod, Irene Tirtajana, Peter Yang and Mathia Lee

Health disparities affecting lesbian, gay, bisexual, transgender and queer (LGBTQ) populations have been reported in many countries. For Singapore, no large quantitative studies…

5454

Abstract

Purpose

Health disparities affecting lesbian, gay, bisexual, transgender and queer (LGBTQ) populations have been reported in many countries. For Singapore, no large quantitative studies on mental health and well-being in the local LGBTQ community have been published. The authors conducted a community-based survey (National LGBT Census Singapore, 2013; NLCS2013) that covered a comprehensive set of demographic, social and health indicators. Here, the authors investigated mental health status and its correlates in 2,350 LGBTQ individuals within the NLCS2013 sample.

Design/methodology/approach

The NLCS2013 was an anonymous online survey conducted amongst self-identified LGBTQ adults (aged ≥ 21 years) residing in Singapore. The survey included the World Health Organisation Well-being Index (WHO-5) as a measure of mental well-being, with low WHO 5 scores (<13/25) indicating poor mental well-being. The authors analysed relationships between low WHO-5 score and a range of respondent characteristics using multivariate logistic regression.

Findings

Strikingly, 40.9% of 2,350 respondents analysed had low WHO-5 scores, indicating poor mental well-being. Parental non-acceptance, experience of conflict at home and bullying/discrimination in the workplace or educational environments were all significantly associated with poor mental well-being. Conversely, community participation appeared protective for mental well-being, as respondents who participated in LGBTQ community organisations or events were less likely to have poor mental well-being than non-participants.

Originality/value

The NLCS2013 represents one of the first broad-based efforts to comprehensively and quantitatively capture the sociodemographic and health profile, including mental health status, within Singapore’s resident LGBTQ population. These findings affirm the need to address the mental health needs of LGBTQ individuals in Singapore and to foster safe spaces and allyship.

Details

Equality, Diversity and Inclusion: An International Journal, vol. 42 no. 5
Type: Research Article
ISSN: 2040-7149

Keywords

Open Access
Article
Publication date: 10 November 2023

Alessandro Gabrielli and Giulio Greco

Drawing on the resource-based view (RBV), this study investigates how tax planning affects the likelihood of financial default in different stages of the corporate life cycle.

Abstract

Purpose

Drawing on the resource-based view (RBV), this study investigates how tax planning affects the likelihood of financial default in different stages of the corporate life cycle.

Design/methodology/approach

Collecting a large sample of US firms between 1989 and 2016, hypotheses are tested using a hazard model. Several robustness and endogeneity checks corroborate the main findings.

Findings

The results show that tax-planning firms are less likely to default in the introduction and decline stages, while they are more likely to default in the growth and maturity stages. The findings suggest that introductory and declining firms use cash resources obtained from tax planning efficiently to meet their needs and acquire other useful resources. In growing and mature firms, tax aggressiveness generates unnecessary slack resources, weakens managerial discipline and increases reputational risks.

Practical implications

The results shed light on the benefits and costs associated with tax planning throughout firms' life cycle, holding great significance for managers, investors, lenders and other stakeholders.

Originality/value

This study contributes to the literature that examines resource management at different life cycle stages by showing that cash resources from tax planning are managed in distinctive ways in each life cycle stage, having a varied impact on the likelihood of default. The authors shed light on underexplored cash resources. Furthermore, this study shows the potential linkages between the agency theory and RBV.

Details

Management Decision, vol. 61 no. 13
Type: Research Article
ISSN: 0025-1747

Keywords

Open Access
Article
Publication date: 6 February 2023

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…

9293

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.

Details

Journal of Enterprise Information Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1741-0398

Keywords

Open Access
Article
Publication date: 25 January 2024

Joseph Kuruneri and Wiston Zivanai

Governments worldwide seek to optimize value in public project bids. Social procurement (SP) has become a global tool for achieving project goals. The purpose of this study is to…

Abstract

Purpose

Governments worldwide seek to optimize value in public project bids. Social procurement (SP) has become a global tool for achieving project goals. The purpose of this study is to assess the understanding of SP among contractors and identify its drivers to optimize the value associated with public projects.

Design/methodology/approach

A total of 15 major contractors were interviewed to obtain their views on SP, appreciate their current practices and identify the main drivers of SP in projects. A semistructured interview was used to gather relevant data. Neo-institutional theory is the lens of the study used to provide the focus of the research. The collected data were analyzed using the thematic data analysis technique.

Findings

The study found that SP is understood as corporate social responsibility and is not handled in a structured manner guided by policies or clearly defined procedures. Additionally, research has shown that compliance requirements, rather than value and goodwill, are the main inspiration for SP practices.

Research limitations/implications

The study’s limitation is the fact that it was conducted in the context of Botswana and only used the interview technique as the solo data collection method. The other limitation is the lack of empirical literature on SP concerning the lack of SP policy in Botswana.

Originality/value

This study raises awareness of the concept of SP among contractors in Botswana and eases its implementation within the industry.

Details

Modern Supply Chain Research and Applications, vol. 6 no. 1
Type: Research Article
ISSN: 2631-3871

Keywords

Open Access
Article
Publication date: 28 July 2020

Xisto L. Travassos, Sérgio L. Avila and Nathan Ida

Ground Penetrating Radar is a multidisciplinary Nondestructive Evaluation technique that requires knowledge of electromagnetic wave propagation, material properties and antenna…

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Abstract

Ground Penetrating Radar is a multidisciplinary Nondestructive Evaluation technique that requires knowledge of electromagnetic wave propagation, material properties and antenna theory. Under some circumstances this tool may require auxiliary algorithms to improve the interpretation of the collected data. Detection, location and definition of target’s geometrical and physical properties with a low false alarm rate are the objectives of these signal post-processing methods. Basic approaches are focused in the first two objectives while more robust and complex techniques deal with all objectives at once. This work reviews the use of Artificial Neural Networks and Machine Learning for data interpretation of Ground Penetrating Radar surveys. We show that these computational techniques have progressed GPR forward from locating and testing to imaging and diagnosis approaches.

Details

Applied Computing and Informatics, vol. 17 no. 2
Type: Research Article
ISSN: 2634-1964

Keywords

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