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Available. Open Access. Open Access
Article
Publication date: 21 September 2022

Catherine Mawia Mwema, Netsayi Noris Mudege and Keagan Kakwasha

While the literature has highlighted the impacts of COVID-19, there is limited evidence on the gendered determinants of the impact of COVID-19 among small-scale rural traders in…

1205

Abstract

Purpose

While the literature has highlighted the impacts of COVID-19, there is limited evidence on the gendered determinants of the impact of COVID-19 among small-scale rural traders in developing and emerging economies.

Design/methodology/approach

Cross-border fish traders who had operated before and during the COVID-19 pandemic were interviewed in a survey conducted in Zambia and Malawi. Logistic regressions among male and female traders were employed to assess the gendered predictors.

Findings

Heterogeneous effects in geographical location, skills, and knowledge were reported among male cross-border traders. Effects of household structure and composition significantly influenced the impact of COVID-19 among female traders. Surprisingly, membership in trade associations was associated with the high impact of COVID-19.

Research limitations/implications

Due to the COVID-19 pandemic and the migratory nature of cross-border fish traders, the population of cross-border fish traders at the time of the study was unknown and difficult to establish, cross-border fish traders (CBFT) at the landing sites and market areas were targeted for the survey without bias.

Originality/value

This paper addresses a gap in the literature on understanding gendered predictors of the impacts of COVID-19 among small-scale cross-border traders.

Details

Journal of Agribusiness in Developing and Emerging Economies, vol. 14 no. 4
Type: Research Article
ISSN: 2044-0839

Keywords

Available. Open Access. Open Access
Article
Publication date: 5 March 2021

Xuan Ji, Jiachen Wang and Zhijun Yan

Stock price prediction is a hot topic and traditional prediction methods are usually based on statistical and econometric models. However, these models are difficult to deal with…

17615

Abstract

Purpose

Stock price prediction is a hot topic and traditional prediction methods are usually based on statistical and econometric models. However, these models are difficult to deal with nonstationary time series data. With the rapid development of the internet and the increasing popularity of social media, online news and comments often reflect investors’ emotions and attitudes toward stocks, which contains a lot of important information for predicting stock price. This paper aims to develop a stock price prediction method by taking full advantage of social media data.

Design/methodology/approach

This study proposes a new prediction method based on deep learning technology, which integrates traditional stock financial index variables and social media text features as inputs of the prediction model. This study uses Doc2Vec to build long text feature vectors from social media and then reduce the dimensions of the text feature vectors by stacked auto-encoder to balance the dimensions between text feature variables and stock financial index variables. Meanwhile, based on wavelet transform, the time series data of stock price is decomposed to eliminate the random noise caused by stock market fluctuation. Finally, this study uses long short-term memory model to predict the stock price.

Findings

The experiment results show that the method performs better than all three benchmark models in all kinds of evaluation indicators and can effectively predict stock price.

Originality/value

In this paper, this study proposes a new stock price prediction model that incorporates traditional financial features and social media text features which are derived from social media based on deep learning technology.

Details

International Journal of Crowd Science, vol. 5 no. 1
Type: Research Article
ISSN: 2398-7294

Keywords

Available. Open Access. Open Access
Article
Publication date: 10 April 2023

Loretta Mastroeni, Maurizio Naldi and Pierluigi Vellucci

Though the circular economy (CE) is a current buzzword, this still lacks a precise definition. In the absence of a clear notion of what that term includes, actions taken by the…

1708

Abstract

Purpose

Though the circular economy (CE) is a current buzzword, this still lacks a precise definition. In the absence of a clear notion of what that term includes, actions taken by the government and companies may not be well informed. In particular, those actions need to consider what people mean when people talk about the CE, either to refocus people's decisions or to undertake a more effective communications strategy.

Design/methodology/approach

Since people voice people's opinions mainly through social media nowadays, special attention has to be paid to discussions on those media. In this paper, the authors focus on Twitter as a popular social platform to deliver one's thoughts quickly and fast. The authors' research aim is to get the perceptions of people about the CE. After collecting more than 100,000 tweets over 16 weeks, the authors analyse those tweets to understand the public discussion about the CE. The authors conduct a frequency analysis of the most recurring words, including the words' association with other words in the same context and categorise them into a set of topics.

Findings

The authors show that the discussion focuses on the usage of resources and materials that heavily endanger sustainability, i.e. carbon and plastic and the harmful habit of wasting. On the other hand, the two most common good practices associated with the CE and sustainability emerge as recycling and reuse (the latter being mentioned far less). Also, the business side of the CE appears to be relevant.

Research limitations/implications

The outcome of this analysis can drive suitable communication strategies by which companies and governments interested in the development of the CE can understand what is actually discussed on social media and call for the attention.

Originality/value

This paper addresses the lack of a standard definition the authors highlighted in the Introduction. The results confirm that people understand CE by looking both at CE's constituent activities and CE's expected consequences, namely the reduction of waste, the transition to a green economy free of plastic and other pollutants and the improvement of the world climate.

Details

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

Keywords

Available. Open Access. Open Access
Article
Publication date: 15 May 2023

Huong Ha and C.K. Peter Chuah

The purpose of this paper is to (a) examine the current state of the digital economy in Southeast Asia (SEA), the challenges and opportunities derived from digital transformation…

14674

Abstract

Purpose

The purpose of this paper is to (a) examine the current state of the digital economy in Southeast Asia (SEA), the challenges and opportunities derived from digital transformation and the digital economy, and the impact of the digital economy on SEA, especially human and physical capital development, and (b) propose policy recommendations for SEA countries to better manage digital transformation.

Design/methodology/approach

This is a conceptual paper. The theoretical framework has been built from the three-sector governance approach to identify the issues of the digital economy and propose solutions to address the issues. Specifically, it examines the role and activities of the public sector, the private sector and the third sector to address the challenges posed by the digital economy, especially human and physical capital development.

Findings

This paper revealed challenges and opportunities derived from the experience of Southeast Asian countries and proposed several policies recommendations, including a common data policy and payment platform for the Asian region, a good training and development policy to equip the workforce with digital skills, and digital mindset as well as build cybersecurity capability and capacity at the regional level.

Originality/value

This paper is significant as it examines the development of the digital economy from an interdisciplinary perspective – including economics, digitalisation, governance, management, public policy, technology and human resource development. It also provides better insights into how SEA's digital economic development can be further improved to contribute to a sustainable regional economy.

Available. Open Access. Open Access
Article
Publication date: 30 March 2023

Areej Alyami, David Sammon, Karen Neville and Carolanne Mahony

This study explores the critical success factors (CSFs) for Security Education, Training and Awareness (SETA) program effectiveness. The questionable effectiveness of SETA…

5382

Abstract

Purpose

This study explores the critical success factors (CSFs) for Security Education, Training and Awareness (SETA) program effectiveness. The questionable effectiveness of SETA programs at changing employee behavior and an absence of empirical studies on the CSFs for SETA program effectiveness is the key motivation for this study.

Design/methodology/approach

This exploratory study follows a systematic inductive approach to concept development. The methodology adopts the “key informant” approach to give voice to practitioners with SETA program expertise. Data are gathered using semi-structured interviews with 20 key informants from various geographic locations including the Gulf nations, Middle East, USA, UK and Ireland.

Findings

In this study, the analysis of these key informant interviews, following an inductive open, axial and selective coding approach, produces 11 CSFs for SETA program effectiveness. These CSFs are mapped along the phases of a SETA program lifecycle (design, development, implementation and evaluation) and nine relationships identified between the CSFs (within and across the lifecycle phases) are highlighted. The CSFs and CSFs' relationships are visualized in a Lifecycle Model of CSFs for SETA program effectiveness.

Originality/value

This research advances the first comprehensive conceptualization of the CSFs for SETA program effectiveness. The Lifecycle Model of CSFs for SETA program effectiveness provides valuable insights into the process of introducing and sustaining an effective SETA program in practice. The Lifecycle Model contributes to both theory and practice and lays the foundation for future studies.

Details

Information Technology & People, vol. 36 no. 8
Type: Research Article
ISSN: 0959-3845

Keywords

Available. Open Access. Open Access
Article
Publication date: 9 September 2024

Michael Wayne Davidson, John Parnell and Shaun Wesley Davenport

The purpose of this study is to address a critical gap in enterprise resource planning (ERP) implementation process for small and medium-sized enterprises (SMEs) by acknowledging…

775

Abstract

Purpose

The purpose of this study is to address a critical gap in enterprise resource planning (ERP) implementation process for small and medium-sized enterprises (SMEs) by acknowledging and countering cognitive biases through a cognitive bias awareness matrix model. Cognitive biases such as temporal discounting and optimism bias often skew decision-making, leading SMEs to prioritize short-term benefits over long-term sustainability or underestimate the challenges involved in ERP implementation. These biases can result in costly missteps, underutilizing ERP systems and project failure. This study enhances decision-making processes in ERP adoption by introducing a matrix that allows SMEs to self-assess their level of awareness and proactivity when addressing cognitive biases in decision-making.

Design/methodology/approach

The design and methodology of this research involves a structured approach using the problem-intervention-comparison-outcome-context (PICOC) framework to systematically explore the influence of cognitive biases on ERP decision-making in SMEs. The study integrates a comprehensive literature review, empirical data analysis and case studies to develop the Cognitive Bias Awareness Matrix. This matrix enables SMEs to self-assess their susceptibility to biases like temporal discounting and optimism bias, promoting proactive strategies for more informed ERP decision-making. The approach is designed to enhance SMEs’ awareness and management of cognitive biases, aiming to improve ERP implementation success rates and operational efficiency.

Findings

The findings underscore the profound impact of cognitive biases and information asymmetry on ERP system selection and implementation in SMEs. Temporal discounting often leads decision-makers to favor immediate cost-saving solutions, potentially resulting in higher long-term expenses due to the lack of scalability. Optimism bias tends to cause underestimating risks and overestimating benefits, leading to insufficient planning and resource allocation. Furthermore, information asymmetry between ERP vendors and SME decision-makers exacerbates these biases, steering choices toward options that may not fully align with the SME’s long-term interests.

Research limitations/implications

The study’s primary limitation is its concentrated focus on temporal discounting and optimism bias, potentially overlooking other cognitive biases that could impact ERP decision-making in SMEs. The PICOC framework, while structuring the research effectively, may restrict the exploration of broader organizational and technological factors influencing ERP success. Future research should expand the range of cognitive biases and explore additional variables within the ERP implementation process. Incorporating a broader array of behavioral economic principles and conducting longitudinal studies could provide a more comprehensive understanding of the challenges and dynamics in ERP adoption and utilization in SMEs.

Practical implications

The practical implications of this study are significant for SMEs implementing ERP systems. By adopting the Cognitive Bias Awareness Matrix, SMEs can identify and mitigate cognitive biases like temporal discounting and optimism bias, leading to more rational and effective decision-making. This tool enables SMEs to shift focus from short-term gains to long-term strategic benefits, improving ERP system selection, implementation and utilization. Regular use of the matrix can help prevent costly implementation errors and enhance operational efficiency. Additionally, training programs designed around the matrix can equip SME personnel with the skills to recognize and address biases, fostering a culture of informed decision-making.

Social implications

The study underscores significant social implications by enhancing decision-making within SMEs through cognitive bias awareness. By mitigating biases like temporal discounting and optimism bias, SMEs can make more socially responsible decisions, aligning their business practices with long-term sustainability and ethical standards. This shift improves operational outcomes and promotes a culture of accountability and transparency. The widespread adoption of the Cognitive Bias Awareness Matrix can lead to a more ethical business environment, where decisions are made with a deeper understanding of their long-term impacts on employees, customers and the broader community, fostering trust and sustainability in the business ecosystem.

Originality/value

This research introduces the original concept of the Cognitive Bias Awareness Matrix, a novel tool designed specifically for SMEs to evaluate and mitigate cognitive biases in ERP decision-making. This matrix fills a critical gap in the existing literature by providing a structured, actionable framework that effectively empowers SMEs to recognize and address biases such as temporal discounting and optimism bias. Its practical application promises to enhance decision-making processes and increase the success rates of ERP implementations. This contribution is valuable to behavioral economics and information systems, offering a unique approach to integrating cognitive insights into business technology strategies.

Details

Journal of Ethics in Entrepreneurship and Technology, vol. 4 no. 1
Type: Research Article
ISSN: 2633-7436

Keywords

Available. Open Access. Open Access
Article
Publication date: 16 October 2017

Xiang T.R. Kong, Ray Y. Zhong, Gangyan Xu and George Q. Huang

The purpose of this paper is to propose a concept of cloud auction robot (CAR) and its execution platform for transforming perishable food supply chain management. A new paradigm…

3462

Abstract

Purpose

The purpose of this paper is to propose a concept of cloud auction robot (CAR) and its execution platform for transforming perishable food supply chain management. A new paradigm of goods-to-person auction execution model is proposed based on CARs. This paradigm can shift the management of traditional manual working to automated execution with great space and time saving. A scalable CAR-enabled execution system (CARES) is presented to manage logistics workflows, tasks and behavior of CAR-Agents in handling the real-time events and associated data.

Design/methodology/approach

An Internet of Things enabled auction environment is designed. The robot is used to pick up and deliver the auction products and commends are given to the robot in real-time. CARES architecture is proposed while integrating three core services from auction workflow management, auction task management, to auction execution control. A system prototype was developed to show its execution through physical emulations and experiments.

Findings

The CARES could well schedule the tasks for each robot to minimize their waiting time. The total execution time is reduced by 33 percent on average. Space utilization for each auction studio is improved by about 50 percent per day.

Originality/value

The CAR-enabled execution model and system is simulated and verified in a ubiquitous auction environment so as to upgrade the perishable food supply chain management into a new level which is automated and real-time. The proposed system is flexible to cope with different auction scenarios, such as different auction mechanisms and processes, with high reconfigurability and scalability.

Details

Industrial Management & Data Systems, vol. 117 no. 9
Type: Research Article
ISSN: 0263-5577

Keywords

Available. Open Access. Open Access
Article
Publication date: 27 September 2023

Eva Wagner, Helmut Pernsteiner and Aisha Riaz

This study aims to provide insights into gender diversity in Pakistani boardrooms, particularly for the dominant family business type, which is strongly guided by (non-financial…

1243

Abstract

Purpose

This study aims to provide insights into gender diversity in Pakistani boardrooms, particularly for the dominant family business type, which is strongly guided by (non-financial) family-related objectives when making business decisions, such as the appointment of board members. Pakistani companies operate within the framework of weak legal institutions and a traditionally highly patriarchal environment. This study examines how corporate decisions regarding the appointment of female board members play out in this socio-political and cultural environment.

Design/methodology/approach

Board composition and board characteristics were examined using hand-collected data from 213 listed family firms and non-family firms on the Pakistan Stock Exchange from 2003 to 2017. Univariate analyses, probit regressions and robustness tests were performed.

Findings

Pakistani family firms have a significantly higher proportion of women on their boards than do non-family firms. They are also significantly more likely to appoint women to top positions, such as CEO or chairs.

Practical implications

Evidently, women are allowed to enter boards through family affiliations. Gender quotas appear an ineffective instrument for breaking through the “glass ceiling” in this socio-cultural environment. Thus, gender parity must entail the comprehensive promotion of women and the enforcement of legal reforms for structural and cultural change.

Originality/value

The analysis focuses on a Muslim-majority emerging Asian market that has been scarcely researched, thus offering new perspectives and insights into board composition and corporate governance that go beyond the well-studied Western countries.

Details

Gender in Management: An International Journal , vol. 39 no. 4
Type: Research Article
ISSN: 1754-2413

Keywords

Available. Open Access. Open Access
Article
Publication date: 30 November 2021

Federico Barravecchia, Luca Mastrogiacomo and Fiorenzo Franceschini

Digital voice-of-customer (digital VoC) analysis is gaining much attention in the field of quality management. Digital VoC can be a great source of knowledge about customer needs…

2264

Abstract

Purpose

Digital voice-of-customer (digital VoC) analysis is gaining much attention in the field of quality management. Digital VoC can be a great source of knowledge about customer needs, habits and expectations. To this end, the most popular approach is based on the application of text mining algorithms named topic modelling. These algorithms can identify latent topics discussed within digital VoC and categorise each source (e.g. each review) based on its content. This paper aims to propose a structured procedure for validating the results produced by topic modelling algorithms.

Design/methodology/approach

The proposed procedure compares, on random samples, the results produced by topic modelling algorithms with those generated by human evaluators. The use of specific metrics allows to make a comparison between the two approaches and to provide a preliminary empirical validation.

Findings

The proposed procedure can address users of topic modelling algorithms in validating the obtained results. An application case study related to some car-sharing services supports the description.

Originality/value

Despite the vast success of topic modelling-based approaches, metrics and procedures to validate the obtained results are still lacking. This paper provides a first practical and structured validation procedure specifically employed for quality-related applications.

Details

International Journal of Quality & Reliability Management, vol. 39 no. 6
Type: Research Article
ISSN: 0265-671X

Keywords

Available. Open Access. Open Access
Article
Publication date: 31 March 2019

Wai Ching Alice Chu, Man Hin Eve Chan, Jenny Cheung and Hong-Oanh Nguyen

Since its development by Tinbergen (1962), the gravity model of international trade has widely been applied to analyse the effect of various factors on trade relationships between…

821

Abstract

Since its development by Tinbergen (1962), the gravity model of international trade has widely been applied to analyse the effect of various factors on trade relationships between countries. Past studies on trade gravity vary not only in the mix of model variables but also in how they have come into the analysis. This study reviews existing literature on bilateral trade with an aim to identify influential predictors such as changes of trade policy and national development strategy and highlight important yet understudied factors such as transport and logistics infrastructure, and sustainable development. To demonstrate the needs to examine these critical factors across industry sectors, the study presents the case of textiles and clothing (T&C) production and trade between China and its trading partners as an illustration. Through the literature review, it shows how the gravity model can be applied to address current issues in international trade arena such as the potential trade war between the US and China, China’s Belt and Road Initiative (BRI), and other important factors shaping global T&C trade. This study offers future research directions for analysis of global trade in the T&C industry and contributes to the wider literature of international business and trade.

Details

Journal of International Logistics and Trade, vol. 17 no. 1
Type: Research Article
ISSN: 1738-2122

Keywords

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