Now showing items 1-20 of 1243

    • Introducing a new measure of energy transition: Green quality of energy mix and its impact on CO2 emissions

      Lau, C.K.; Gozgor, Giray; Mahalik, M.K.; Patel, G.; Li, Jing (Elsevier, 2023-06)
      This paper introduces a novel measure of the energy transition, i.e., the green quality of energy mix (GREENQ) across the Organisation for Economic Co-operation and Development (OECD) countries. Then, the paper examines the impact of the GREENQ on CO2 emissions in the panel dataset of 36 OECD countries from 1970 to 2021. The explanatory variables include per capita income, institutional quality and technology. Long-run panel data estimations indicate that per capita income, institutional quality and technology increase CO2 emissions. The novel evidence is that the GREENQ is negatively related to the level of CO2 emissions. These findings are robust to employ different panel data estimation techniques. Potential policy implications are also discussed.
    • Exploring the Academic - Industry Collaboration in Knowledge Sharing for Supplier Selection: Digitalizing the OEM

      Chakraborty, A.; Persis, J.; Mahroof, Kamran (2023)
      Increasing reliance on digital technologies has led to a significant shift in how businesses operate, with many now relying heavily on digital platforms for effective planning, communication, sales, marketing, supply chain, and logistics management. In this context, knowledge sharing platforms enable academic–industry collaboration in which exchange of ideas, opinions, experience, and expertise brings collective intelligence in cooperative learning ecosystem thereby expediting decision making. However, establishing long-term commitment among the partners, allocation of time and resources for sharing tacit knowledge, collaboration among partners with different strategic priorities, and real-time knowledge sharing capabilities are essential for effective and rapid learning in knowledge sharing platforms. The present article will examine these benefits and challenges in knowledge sharing and its impact on supplier selection platforms in Asian automakers. The findings of this article will be helpful for researchers and practitioners intending to explore the role of cooperation in knowledge sharing and digital transformation amid competitive environment prevalent in the automotive industry. The potential supplier database is first examined for qualifying the capability requirements put forth in this article and further prioritized using a multicriteria decision-making technique and analytic hierarchy process. The article results reveal that the manufacturer has highly prioritized firms’ financial transparency for supplier evaluation followed by the suppliers’ cost control, quality control, and manufacturing capabilities. The article has significant theoretical and practical implications for developing robust supplier evaluation criteria for automobile industry and a digital ecosystem for original equipment manufacturers in making supplier related decisions.
    • Examining the impact of resilience strategies in mitigating medicine shortages in the United Kingdom's (UK) pharmaceutical supply chain (PSC)

      Yaroson, E.V.; Breen, Liz; Hou, Jiachen; Sowter, Julie (2023)
      Purpose Medicine shortages have a detrimental impact on stakeholders in the pharmaceutical supply chain (PSC). Existing studies suggest that building resilience strategies can mitigate the effects of these shortages. As such, this research aims to examine whether resilience strategies can reduce the impact of medicine shortages in the United Kingdom's (UK) PSC. Design/methodology/approach A sequential mixed-methods approach that involved qualitative and quantitative research enquiry was employed in this study. The data were collected using semi-structured interviews with 23 key UK PSC actors at the qualitative stage. During the quantitative phase, 106 respondents completed the survey questionnaires. The data were analysed using partial least square-structural equation modelling (PLS-SEM). Findings The results revealed that reactive and proactive elements of resilience strategies helped tackle medicine shortages. Reactive strategies increased relational issues such as behavioural uncertainty, whilst proactive strategies mitigated them. Practical implications The findings suggest that PSC managers and decision-makers can benefit from adopting structural flexibility and proactive strategies, which are cost-effective measures to tackle medicine shortages. Also engaging in strategic alliances as a proactive strategy mitigates relational issues that may arise in a complex supply chain (SC). Originality/value This study is the first to provide empirical evidence of the impact of resilience strategies in mitigating medicine shortages in the UK's PSC.
    • The effect of government support on bureaucracy, COVID-19 resilience and export intensity: Evidence from North Africa

      Onjewu, A.E.; Olan, F.; Nyuur, Richard B.; Paul, S.; Nguyen, H.T.T. (2023-02)
      The literature on the imperativeness of government support for firm survival since the onset of COVID-19 is vast, but scholars have scarcely considered the impact of such assistance on managers' time, nor the extent to which support measures induce resilience and export activity. Accordingly, this study assesses the impact of government support on (1) bureaucracy and (2) resilience using data from 535 Moroccan SMEs. It further evaluates the influence of resilience on direct versus indirect exports, and espouses the institutional voids, resource-based and strategy-creation view to explain the associations through a contingency lens. The results demonstrate that (1) government support increases bureaucracy which, (2) surprisingly triggers and enhances resilience. Furthermore, (3) resilience has a positive impact on direct exports but (4) adversely affects indirect exports. Theoretically, the findings acquiesce extant calls for measurement specificity in export performance. Practically, stakeholders' attention is drawn to the value of managers' time well spent.
    • Entrepreneurial strategic posture and new technology ventures in an emerging economy

      Amankwah-Amoah, J.; Nyuur, Richard B.; Hinson, R.; Kosiba, J.P.; Al-Tabbaa, O.; Cunningham, J.A. (2023-02)
      Purpose: Although start-ups have gained increasing scholarly attention, we lack sufficient understanding of their entrepreneurial strategic posture (ESP) in emerging economies. The purpose of this study is to examine the processes of ESP of new technology venture start-ups (NTVs) in an emerging market context. Design/methodology/approach: In line with grounded theory guidelines and the inductive research traditions, the authors adopted a qualitative approach involving 42 in-depth semi-structured interviews with Ghanaian NTV entrepreneurs to gain a comprehensive analysis at the micro-level on the entrepreneurs' strategic posturing. A systematic procedure for data analysis was adopted. Findings: From the authors' analysis of Ghanaian NTVs, the authors derived a three-stage model to elucidate the nature and process of ESP Phase 1 spotting and exploiting market opportunities, Phase II identifying initial advantages and Phase III ascertaining and responding to change. Originality/value: The study contributes to advancing research on ESP by explicating the process through which informal ties and networks are utilised by NTVs and NTVs' founders to overcome extreme resource constraints and information vacuums in contexts of institutional voids. The authors depart from past studies in demonstrating how such ties can be harnessed in spotting and exploiting market opportunities by NTVs. On this basis, the paper makes original contributions to ESP theory and practice.
    • Online product decision support using sentiment analysis and fuzzy cloud-based multi-criteria model through multiple e-commerce platforms

      Yang, Z.; Li, Q.; Vincent, Charles; Xu, B.; Gupta, S. (2023)
      The competitive landscape of multiple e-commerce platforms and the vast amount of product reviews associated with these platforms have supported both consumers’ online shopping decision making and also served as a reference for product attribute performance improvement. This paper proposes a sentiment-driven fuzzy cloud multi-criteria model for online product ranking and performance to provide purchase recommendations. In this novel model, Bi-directional Long Short-Term Memory Network-Conditional Random Fields (BiLSTM-CRF), sentiment analysis, and K-means clustering are first integrated to mine product attributes and compute sentiment values based on reviews from various platforms. Next, considering the confidence of the sentiment value, the cloud model is combined with q-rung orthopair fuzzy sets to define the new concept of the q-rung orthopair fuzzy cloud (q-ROFC) and the interaction operational laws between q-ROFCs are given. The sentiment values of each product attribute from different platforms are cross-combined and transformed into a type of q- ROFC, while multiple interactive information matrices are established. To investigate the correlation among homogeneous attributes, the q-ROFC interaction weighted partitioned Maclaurin Symmetric mean operator is proposed. Finally, we provide real-world examples of online mobile phone ranking and attribute performance evaluation. The results show that our proposed method offers significant advantages in dealing with customer purchase decisions for online products and problems with performance direction identification. Managerial implications are discussed.
    • Deposit-borrowing substitutability: evidence from microfinance institutions around the world

      Shettima, U.; Dzolkarnaini, Nazam (2023)
      Drawing from 645 microfinance institutions across 56 countries, this paper examines the deposit-borrowing dynamic of microfinance institutions’ source of capital. We find that deposits and borrowings are substitutes rather than complements. We further find that the degree of substitutability is more pronounced among microfinance institutions operating in a developed financial sector where the level of information asymmetry is lower. Our findings represent novel contribution in understanding microfinance institutions’ funding behaviour that supports its quest for further growth and long-term sustainability.
    • Cryptocurrency Risk and Governance Challenges

      Minhat, Marizah; Abdullah, M.; Dzolkarnaini, Nazam; Sapiei, N.S. (Routledge, 2023)
      This book provides an interdisciplinary critical perspective regarding risk, uncertainty, and governance challenges of cryptocurrencies. It considers the perspectives of several disciplines including accounting, cybersecurity, cyberlaw, economics, ethics, finance, financial regulation, shariah (Islamic) law and technology. Distinguished from other books on similar topic, our in-depth analysis and critical discourse on cryptocurrency risk categories are supplemented by research evidence gathered from surveys and interviews with stakeholders. The inclusion of an Islamic insight matters given mixed views at present regarding the permissibility of cryptocurrencies albeit some countries have imposed somewhat restricted function of cryptocurrencies for non-religious reasons. It is envisaged that this book will help enlighten stakeholders on this aspect of uncertainty and inspire fit and proper governance strategies for the public interest.
    • Disruptive market shift: conceptualization, antecedents, and response mechanisms

      Olabode, Oluwaseun E.; Hultman, M.; Boso, N.; Leonidou, C. (2023-07)
      Although prior research has examined the effects of different forms of disruptive market shift on organizational practice, structure, and performance, knowledge is lacking on its conceptual domain, antecedents, and organizational response outcomes. This study draws insights from an in-depth analysis of 23 organizations to conceptualize disruptive market shift and explore its antecedents and consequences. We find that digitization, technological advancements, political uncertainty and government regulations, competitive pressures, the media, and customer dynamism are major drivers of disruptive market shifts. Furthermore, evidence suggests that organizations establish collaborative relationships, initiate internal transformational processes, and develop innovative metrics and patterns to respond to disruptive market shifts. We discuss the theoretical and managerial implications of the findings.
    • A multi-contextual lens on racism and discrimination in the multicultural marketplace

      Galalae, C.; Kipnis, Eva; Cui, C.C.; Johnson, E.; Licsandru, T.; Vorster, L.; Demangeot, C.; Kearney, S.; Mari, C.; Ruiz, V.M.; et al. (2023-01)
      This article highlights the generative properties of context for consumer experiences of racism and discrimination. Drawing from conceptualizations of context in social anthropology and human geography, it develops a framework to systematically catalogue intersections of various micro- and macro-social contexts that configure within and across marketplace geographies and inform racism and discrimination. The framework is applied to an integrative review of studies on marketplace racism and discrimination. The review illuminates that: 1) application of intersectional perspectives varies significantly across cultural difference dimensions; 2) knowledge is clustered within specific micro-social context expressions of cultural difference dimensions; 3) studies intersecting micro- and macro-social expressions commonly reveal underexplored discrimination instances; and 4) knowledge on macro-social contextual forces significantly lacks non-western perspectives. Drawing on the review findings, a list of areas of advancement for future scholarship is presented, along with recommendations for marketing practitioners acting towards identifying, understanding, and counteracting racism and discrimination.
    • Adverse selection in cryptocurrency markets

      Tiniç, M.; Sensoy, A.; Akyildirim, Erdinc; Corbet, S. (2023)
      This paper investigates the influence that information asymmetry may possess upon the future volatility, liquidity, market toxicity and returns within cryptocurrency markets. We use the adverse selection component of the effective spread as a proxy for overall information asymmetry. Using order and trade data from the Bitfinex Exchange, we first document statistically significant adverse selection costs for major cryptocurrencies. Our results also suggest that adverse selection costs, on average, correspond to ten percent of the estimated effective spread, indicating an economically significant impact of adverse selection risk on transaction costs in cryptocurrency markets. We finally document that adverse selection costs are important predictors of intraday volatility, liquidity, market toxicity, and returns.
    • Green light for green credit? Evidence from its impact on bank efficiency

      Galán, J.E.; Tan, Yong (2023)
      We assess, for the first time in the literature, the impact of green credit on bank efficiency. We find that green credit has a negative impact on bank efficiency. However, the effect is heterogeneous among different types of banks. While small and low capitalized banks are more affected, the impact is lower in banks with higher levels of risk. On the other hand, we find that highly capitalized banks can offset the negative effects of green credit, while large banks and those highly involved in green credit, benefit from this activity.
    • Demographic efficiency drivers in the Chinese energy production chain: A hybrid neural multi-activity network data envelopment analysis

      Zhao, Y.; Antunes, J.J.M.; Tan, Yong; Wanke, P.F. (2023)
      For meeting the external requirements of the Paris Agreement and reducing energy consumption per gross domestic product, China needs to improve its energy efficiency. Although the existing studies have attempted to investigate energy efficiency from different perspectives, little effort has yet been made to consider the collaboration among different stages in the production chain to produce energy outputs. In addition, various studies have also examined the determinants of energy efficiency, however, they mainly focused on technology and economic factors, no study has yet proposed and considered the influence of geographical factors on energy efficiency. In this article, we fill in the gap and make theoretical and empirical contributions to the literature. In this study, a two-stage analysis method is used to analyse energy efficiency and the influencing factors in China between 2009 and 2021. More specifically, from the theoretical/methodological perspective, a multi-activity network data envelopment analysis model is used to measure energy efficiency of different processes in the energy production chain. From the empirical perspective, we attempt to investigate the influence of geographical factors on energy efficiency through a neural network analysis. Meanwhile, the comparisons among different provinces are made. The result shows that the overall energy efficiency is low in China, and China relies more on the traditional energy industry than the clean energy industry. The efficiency level experiences a level of volatility over the examined period. Finally, we find that raw fuel pre-process and industry have a significant and positive impact on energy efficiency in China.
    • Dynamic network data envelopment analysis with a sequential structure and behavioural-causal analysis: Application to the Chinese banking industry

      Fukuyama, H.; Tsionas, M.; Tan, Yong (2023-06)
      The current study contributes to the literature in efficiency analysis in two ways: 1) we build on the existing studies in Dynamic Network Data Envelopment Analysis (DNDEA) by proposing a sequential structure incorporating dual-role characteristics of the production factors; 2) we initiate the efforts to complement the proposal of our innovative sequential DNDEA through a behavioural-causal analysis. The proposal of this statistical analysis is very important considering it does not only validate the proposal of the efficiency analysis but also our practice can be generalized to the future studies dealing with designing innovative production process. Finally, we apply these two different analyses to the banking industry. Using a sample of 43 Chinese commercial banks including five different ownership types (state-owned, joint-stock, city, rural, and foreign banks) between 2010 and 2018, we find that the inefficiency level is around 0.14, although slight volatility has been observed. We find that the highest efficiency is dominated by state-owned banks, and although foreign banks are less efficient than joint-stock banks, they are more efficient than city banks. Finally, we find that rural banks have the highest inefficiency.
    • A new perspective on the U.S. energy efficiency: The political context

      Antunes, J.J.M.; Neves, J.C.; Elmor, L.R.C.; Araujo, M.F.R.D.; Wanke, P.F.; Tan, Yong (2023-01)
      This paper offers a new perspective on the energy efficiency literature by bringing evidence of political contextual factors as the predictors of energy efficiency. Specifically, we posit that the Democrat administration is more energy-efficient considering the reduction of environmental impact, in contrast, the Republican administration is more efficient considering only financial expenditures leading to the production of economic growth. In addition, we predict that political administration tenure is negatively correlated with green energy efficiency and that political distancing moderates the relationship between political party administration and energy efficiency. This study sheds light on these matters by performing an efficiency analysis of fifty North American states through a bootstrap DEA non-parametric model, followed by Tobit regressions to evaluate our hypotheses concerning the effect of the contextual factors on the calculated efficiency scores.
    • TEA-IS: A hybrid DEA-TOPSIS approach for assessing performance and synergy in Chinese health care

      Antunes, J.J.M.; Hadi-Vencheh, A.; Jamshidi, A.; Tan, Yong; Wanke, P.F. (2023)
      This paper presents an assessment of the Chinese healthcare system in 31 provinces for a 10-year period in light of relevant physical and human resource variables. First, a novel TEA-IS (Trigonometric Envelopment Analysis for Ideal Solutions) model is developed to assess healthcare efficiency at the province level. Machine learning methods are also employed to predict high-low performance and the synergistic Chinese healthcare province in terms of contextual variables. The results indicate that synergy has played a pivotal role in the Chinese healthcare systems, not only by triggering higher performance levels due to the progressive adoption of best practices over the course of time, but also by being closely related to different socioeconomic and demographic variables, such as the illiteracy rate. It is possible to claim that healthcare performance has remained stable in China over the past two decades, performance and synergy at the province level are still heterogeneous.
    • Estimating market power under a nonparametric analysis: evidence from the Chinese real estate sector

      Fukuyama, H.; Tan, Yong (2022-10)
      The traditional Lerner index is limited in its capacity to estimate the level of competition in the economic sector from the perspective that it mainly focuses on the overall level of market power for each individual decision-making unit. Recently, Fukuyama and Tan (J Oper Res Soc, 73:445–453, 2022) estimated the Lerner index by applying the nonparametric data envelopment analysis (DEA) to calculate the marginal cost, which is an important component in the estimation of the Lerner index. Our study further extends the study of Fukuyama and Tan (J Oper Res Soc, 73:445–453, 2022) by estimating the marginal cost under the DEA in a multi-product setting. Our proposed methodology benefits from the ability to find positive marginal costs for all the products and specifies all decision-making units are profit maximizers. In order to achieve this, the marginal cost is estimated by referring to the nearest point on the best practice cost-efficient frontier for the profit-maximizing firms. We then apply our innovative method to the Chinese real estate industry. The result shows that the Chinese real estate industry has higher market power in the residential commodity housing market than that in the commodity housing market. This is also the case for different geographical areas in China. Overall, for both of these two different markets, the level of market power experiences a level of volatility.
    • Extending the Merton model with applications to credit value adjustment

      Akyildirim, Erdinc; Hekimoglu, A.A.; Sensoy, A.; Fabozzi, F.J. (2023)
      Following the global financial crisis, the measurement of counterparty credit risk has become an essential part of the Basel III accord with credit value adjustment being one of the most prominent components of this concept. In this study, we extend the Merton structural credit risk model for counterparty credit risk calculation in the context of calculating the credit value adjustment mainly by estimating the probability of default. We improve the Merton model in a variance-convoluted-gamma environment to include default dependence between counterparties through a linear factor decomposition framework. This allows one to tackle dependence through a systematic common component. Our set-up allows for easier, faster and more accurate fitting for the credit spread. Results confirm that use of the variance-gamma-convolution clearly solves the vanishing credit spread problem for short time-to-maturity or low leverage cases compared to a Brownian motion environment and its modifications.
    • Examining the Relationship Between Blockchain Capabilities and Organizational Performance in the Indian Banking Sector

      Garg, P.; Gupta, B.; Kapil, K.N.; Sivarajah, Uthayasankar; Gupta, S. (2023-03-20)
      Blockchain has enormous capabilities to transform traditional business models in countless ways. Banks in India are building collaborative blockchain ecosystems to create an innovative business model and disrupt the traditional one to create more competitive advantage. This study’s purpose was to examine the relationship between blockchain capabilities (BCC), competitive advantage (CA), and organizational performance (OP), as well as evaluate CA’s mediating role in the relationship between BCC and OP. In this context, a scientific research model, including a hypothesis, has been developed from extant literature. The proposed model was tested using statistical data collected from blockchain specialists, blockchain product marketing managers, experts in future and emergent technology, and banking, finance, and tech managers or executives who are involved in planning and deploying practical blockchain in the financial sector. Data were analyzed and tested using AMOS 22.0 and a process macro using a sample comprising 289 responses. Our empirical results indicated a significant positive relationship between BCC, CA, and OP, as well as a relationship between BCC and OP, partially mediated by CA. This paper took an original approach and contributes to the literature on this subject to understand CA’s mediating role in the relationship between BCC and OP in the Indian banking sector.
    • Female Board Representation and Coupled Open Innovation: Evidence from Emerging Market Multinational Enterprises

      Adams, Kweku; Attah-Boakye, R.; Yu, H.; Johansson, J.; Njoya, E. (2023-06)
      Little research has been done on female board representation in emerging market multinational enterprises (EMNEs). Our paper considers the role of female board representation and its impact on open innovation (OI) in the unique context of emerging markets. We draw on upper echelons and institutional theories to understand how female board representation and cross-country institutional contexts influence coupled OI. Combining a 10-year (2009-2019) dataset with a rich in-depth content analysis of 183 (EMNEs) engaged in OI, our results reveal a significant positive association between female board representation and a firm’s commitment to coupled OI initiatives. We also find that country-level institutional factors affect and positively moderate the relationship between female board representation and coupled OI. In emerging market environments where managerial perception and cultural beliefs sometimes hinder the promotion of females into top positions, our work has implications for EMNEs regarding how they harness diversity. We contribute to the OI literature by showing that female board representation enhances corporate OI investment within EMNEs.