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1 – 10 of 134The COVID-19 pandemic, a sudden and disruptive external shock to the USA and global economy, profoundly affected various operations. Thus, it becomes imperative to investigate the…
Abstract
Purpose
The COVID-19 pandemic, a sudden and disruptive external shock to the USA and global economy, profoundly affected various operations. Thus, it becomes imperative to investigate the repercussions of this pandemic on the US housing market. This study investigates the impact of the COVID-19 pandemic on a crucial facet of the real estate market: the Time on the Market (TOM). Therefore, this study aims to ascertain the net effect of this unprecedented event after controlling for economic influences and real estate market variations.
Design/methodology/approach
Monthly time series data were collected for the period of January 2010 through December 2022 for statistical analysis. Given the temporal nature of the data, we conducted the Durbin–Watson test on the OLS residuals to ascertain the presence of autocorrelation. Subsequently, we used the generalized regression model to mitigate any identified issues of autocorrelation. However, it is important to note that the response variable derived from count data (specifically, the median number of months), which may not conform to the normality assumption associated with standard regression models. To better accommodate this, we opted to use Poisson regression as an alternative approach. Additionally, recognizing the possibility of overdispersion in the count data, we also explored the application of the negative binomial model as a means to address this concern, if present.
Findings
This study’s findings offer an insightful perspective on the housing market’s resilience in the face of COVID-19 external shock, aligning with previous research outcomes. Although TOM showed a decrease of around 10 days with standard regression and 27% with Poisson regression during the COVID-19 pandemic, it is noteworthy that this reduction lacked statistical significance in both models. As such, the impact of COVID-19 on TOM, and consequently on the housing market, appears less dramatic than initially anticipated.
Originality/value
This research deepens our understanding of the complex lead–lag relationships between key factors, ultimately facilitating an early indication of housing price movements. It extends the existing literature by scrutinizing the impact of the COVID-19 pandemic on the TOM. From a pragmatic viewpoint, this research carries valuable implications for real estate professionals and policymakers. It equips them with the tools to assess the prevailing conditions of the real estate market and to prepare for potential shifts in market dynamics. Specifically, both investors and policymakers are urged to remain vigilant in monitoring changes in the inventory of houses for sale. This vigilant approach can serve as an early warning system for upcoming market changes, helping stakeholders make well-informed decisions.
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Sean MacIntyre, Michael McCord, Peadar T. Davis, Aggelos Zacharopoulos and John A. McCord
The purpose of this study is to examine whether PV uptake is associated with key housing market determinants and linked to socio-economic profiles. An abundance of extant…
Abstract
Purpose
The purpose of this study is to examine whether PV uptake is associated with key housing market determinants and linked to socio-economic profiles. An abundance of extant literature has examined the role of solar photovoltaic (PV) adoption and user costs, with an emerging corpus of literature investigating the role of the determinants of PV uptake, particularly in relation to the built environment and the spatial variation of PV dependency and dissimilarity. Despite this burgeoning literature, there remains limited insights from the UK perspective on housing market characteristics driving PV adoption and in relation spatial differences and heterogeneity that may exist.
Design/methodology/approach
Applying micro-based data at the Super Output Area-level geography, this study develops a series of ordinary least squares, spatial econometric models and a logistic regression analysis to examine built environment, housing tenure and deprivation attributes on PV adoption at the regional level in Northern Ireland, UK.
Findings
The findings emerging from the research reveal the presence of some spatial clustering and PV diffusion, in line with several existing studies. The findings demonstrate that an urban-rural dichotomy exists seemingly driven by social interaction and peer effects which has a profound impact on the likelihood of PV adoption. Further, the results exhibit tenure composition and “economic status” to be significant and important determinants of PV diffusion and uptake.
Originality/value
Housing market characteristics such as tenure composition across local market structures remain under-researched in relation to renewable energy uptake and adoption. This study examines the role of housing market attributes relative to socio-economic standing for adopting renewable energy.
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Musa Ghazwani, Ibrahim Alamir, Rami Ibrahim A. Salem and Nedal Sawan
This study aims to examine the impact of corporate governance (CG) on anti-corruption disclosure (A-CD), paying particular attention to the FTSE 100. Notably, it examines how…
Abstract
Purpose
This study aims to examine the impact of corporate governance (CG) on anti-corruption disclosure (A-CD), paying particular attention to the FTSE 100. Notably, it examines how board and audit committees’ characteristics affect the quantity and quality of anti-corruption disclosure.
Design/methodology/approach
Data from FTSE 100 firms, spanning the period from 2014 to 2020, were analysed using the regression of the Poisson fixed effect and GEE analyses.
Findings
The findings show that gender diversity, audit committee expertise and the independence of the audit committee are positively associated with both quantity and quality of anti-corruption disclosure. Notably, no statistically significant relationships were identified between anti-corruption disclosure and factors such as board size, role duality or board meetings.
Research limitations/implications
The findings provide valuable insights for decision-makers and regulatory bodies, shedding light on the elements that compel UK companies to enhance their anti-corruption disclosure and governance protocols to alleviate corruption and propel efforts towards ethical behaviour.
Originality/value
This study makes a notable contribution to the sparse body of evidence by examining the influence of board and audit committee attributes on anti-corruption disclosure subsequent to the implementation of the UK Bribery Act in 2010. Specifically, to the best of the authors’ knowledge, this study assesses for the first time the impact of board and audit committee mechanisms on both the quantity and quality of anti-corruption disclosure.
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Aulona Ulqinaku, Selma Kadić-Maglajlić and Gülen Sarial-Abi
Today, individuals use social media to express their opinions and feelings, which offers a living laboratory to researchers in various fields, such as management, innovation…
Abstract
Purpose
Today, individuals use social media to express their opinions and feelings, which offers a living laboratory to researchers in various fields, such as management, innovation, technology development, environment and marketing. It is therefore necessary to understand how the language used in user-generated content and the emotions conveyed by the content affect responses from other social media users.
Design/methodology/approach
In this study, almost 700,000 posts from Twitter (as well as Facebook, Instagram and forums in the appendix) are used to test a conceptual model grounded in signaling theory to explain how the language of user-generated content on social media influences how other users respond to that communication.
Findings
Extending developments in linguistics, this study shows that users react negatively to content that uses self-inclusive language. This study also shows how emotional content characteristics moderate this relationship. The additional information provided indicates that while most of the findings are replicated, some results differ across social media platforms, which deserves users' attention.
Originality/value
This article extends research on Internet behavior and social media use by providing insights into how the relationship between self-inclusive language and emotions affects user responses to user-generated content. Furthermore, this study provides actionable guidance for researchers interested in capturing phenomena through the social media landscape.
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Paresh Kumar Sarma, Mohammad Jahangir Alam, Ismat Ara Begum and Sheikh Mohammad Sayem
This study aims to investigate the determinants of the food security status of participants and non-participants of livestock extension services living under similar socioeconomic…
Abstract
Purpose
This study aims to investigate the determinants of the food security status of participants and non-participants of livestock extension services living under similar socioeconomic conditions as livestock farming households in the Feed the Future zone of Bangladesh.
Design/methodology/approach
Cross-sectional data of 906 farm-households extracted from a total of 2064 from the Feed the Future representative Bangladesh Integrated Households Survey 2018 were used. A triple hurdle model combined with a structural equation model were used to analyze the data. The causal relationship between food security status, livestock extension services, technology adoption and women's empowerment was investigated by estimating structural equation modeling with second-order latent factors.
Findings
The results indicate that livestock extension services have increased livestock technology adoption and have a positively significant (p < 0.01) relationship with household wealth, food security, welfare and women's empowerment.
Originality/value
The results suggest that livestock extension services have an impact on new technology adoption and enhancing women's empowerment; thus, the services should be widely made available in the region.
Peer review
The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-11-2021-0647.
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Domenico Marino, Jaime Gil Lafuente and Domenico Tebala
The objective of this paper is to analyze the relationship between innovation and the development of artificial intelligence (AI) and digital technologies in Europe. The use of…
Abstract
Purpose
The objective of this paper is to analyze the relationship between innovation and the development of artificial intelligence (AI) and digital technologies in Europe. The use of digital technologies among European companies is studied through a composite index, while the relationship between innovation and AI is studied through a log-linear regression model. The results of the model have made possible to develop interesting indications for economic and industrial policy.
Design/methodology/approach
The use of digital technologies among European companies is studied through a composite index of AI and information technology (ICT) (using the Fair and Sustainable Welfare methodology) with the aim of measuring territorial gaps and to know which European countries are more or less inclined to its use, while the relationship between innovation and AI is studied through a log-linear regression model.
Findings
In the paper, two different methodologies were used to analyze the relationship between innovation and the development of digital technologies in Europe. The synthetic indicator made possible to develop a taxonomy between the different countries, the log-linear model made possible to identify and explain the determinants of innovation.
Originality/value
The description of the biunivocal relationship between innovation and AI is a topical and relevant issue that is treated in the paper in an original way using a synthetic indicator and a log-linear model.
研究目的
本文旨在探討在歐洲、創新與人工智能和數字技術的發展之間的關係。研究人員透過一個綜合指數、去探討歐洲公司之間數字技術的使用狀況。至於創新與人工智能之間的關係, 則以對數線性回歸模型來進行研究。從模型所得的結果, 為我們提供了建議、去訂定適切的經濟和產業政策。
研究設計/方法/理念
研究人員透過一個人工智能和資訊科技的綜合指數, 去探討歐洲企業之間數字技術的使用狀況 (研究人員使用了公平和可持續福利方法論), 其目標為測量領土差距, 以及確定哪些歐洲國家、大體上傾向於使用數字技術;至於創新與人工智能之間的關係, 則以對數性回歸模型來進行研究。
研究結果
本文使用了兩個不同的方法、去探討在歐洲、創新與數字技術發展之間的關係。有關的合成指標, 使研究人員可製定一個不同國家間的分類法;而有關的對數線性模型, 則讓研究人員可確立並說明創新的決定因素。
研究的原創性/價值
本文使用了合成指標和對數線性模型、去探討創新與人工智能之間的一對一的關係, 這是時下受到關注和適宜的課題;就研究法而言, 本研究確是新穎獨創的。
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Zhen Luo, Julie Callaert, Deming Zeng and Bart Van Looy
Shifting focus from innovation quantity to innovation quality becomes a priority in innovation study, business and policy. This paper aims to figure out whether and how knowledge…
Abstract
Purpose
Shifting focus from innovation quantity to innovation quality becomes a priority in innovation study, business and policy. This paper aims to figure out whether and how knowledge recombination (recombinant exploration/recombinant exploitation) affects firms' innovation quality (technological value/economic value) and how these relationships are moderated by environmental turbulence (technological turbulence/market turbulence) in the context of open innovation.
Design/methodology/approach
A panel data set is built on 373 Chinese pharmaceutical firms' patents and new product data from 1997 to 2020. And a negative binomial regression model is applied to test the hypotheses.
Findings
The analyses indicate that (1) recombinant exploration favors technological value but hinders economic value, while (2) recombinant exploitation benefits both. Regarding environmental turbulence's moderating effects, (3) technological turbulence has opposite moderating effects on the impacts of recombinant exploration versus exploitation on technological value, whereas (4) market turbulence benefits the impacts of both on economic value.
Practical implications
This research provides the answer to practitioners' question that “How to improve innovation quality?” That is “Think from a recombination logic, clarify your internal value preference and the external turbulence.”
Originality/value
From an emerging perspective of innovation, this research expands the innovation quality research to a recombination logic. A multi-dimensional research framework is developed to clarify the complex relationships between knowledge recombination and innovation quality. Finally, two moderators, technological versus market turbulence, formulate more targeted implications for firms' innovation management in open innovation.
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Anuradha Saikia, Sharad Nath Bhattacharya and Rohit Dwivedi
This study reviews the literature on institutional theory in international business and examines the institutional factors behind the success or failure of multinational…
Abstract
Purpose
This study reviews the literature on institutional theory in international business and examines the institutional factors behind the success or failure of multinational corporations (MNCs) in emerging markets.
Design/methodology/approach
This systematic literature review analysed 116 peer-reviewed articles published in leading journals between 2005 and 2022. The R package Bibliometrix and VOSviewer visualization software were used for analysis. A hybrid methodology combining bibliometric and content analyses was utilized to obtain a descriptive evaluation of the publication impact along with a keyword co-occurrence map, context-specific institutional effects and subsidiary strategies.
Findings
The Journal of International Business Studies, along with influential authors such as Mike W. Peng, Klaus Meyer, and Mehmet Demirbag, have taken the lead in advancing institutional theories for MNC internationalization in emerging markets. The clusters from the co-word analysis revealed dominant MNC entry modes, institutional distances and MNC localization strategies. The content analysis highlights how the institutional environment is operationalized across the macro-, micro- and meso-institutional contexts and how the MNC subsidiary responds in emerging markets. Meso-level interactions emphasize the relational aspects of business strategies in emerging markets.
Practical implications
Contextualizing subsidiary strategies and institutional forms can help managers align their strategic responses to the dynamic relationship between subsidiaries and the institutional environment. The review findings will enable policymakers to simplify regulatory policies and encourage MNC subsidiary networks with local stakeholders in emerging markets.
Social implications
Legitimacy strategies such as corporate community involvement in emerging markets are crucial for enhancing societal support and removing stakeholders' scepticism for MNC business operations in emerging markets. Moral legitimacy should be implemented by managers, such as lending support to disaster management efforts and humanitarian crises, as they expand to new business environments of emerging markets.
Originality/value
This study is the first to explore institutional diversity and subsidiary strategic responses in a three-layered institutional context. The findings highlight the relevance of contextualizing institutional perspectives for international business scholars and practitioners as they help build context-specific theoretical frameworks and business strategies. Future research recommendations are suggested in the macro-, micro- and meso-institutional contexts.
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Junping Qiu, Qinze Mi, Zhongyang Xu, Tingyong Zhang and Tao Zhou
Based on the social interaction theory and trust theory, this study investigates the switching of users on social question and answer (Q&A) platforms from knowledge seekers to…
Abstract
Purpose
Based on the social interaction theory and trust theory, this study investigates the switching of users on social question and answer (Q&A) platforms from knowledge seekers to knowledge contributors.
Design/methodology/approach
We used Python to gather data from Zhihu, performed hypothesis testing on the models using Poisson regression and finally conducted a mediation effect analysis.
Findings
The findings reveal that knowledge seeking impacts users' motivation for information interaction, emotional interaction and trust. Notably, information interaction and trust exhibit a chained mediation effect that subsequently influences knowledge contribution.
Originality/value
Current studies on user knowledge behavior typically examine individual actions, rarely connecting knowledge seeking and knowledge contribution. However, the balance of knowledge inflow and outflow is crucial for social Q&A platforms. To cover this gap, this paper empirically investigates the switching between knowledge seeking and knowledge contribution based on the social interaction theory and trust theory.
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Haden Comstock and Nathan DeLay
Climate change is expected to cause larger and more frequent precipitation events in key agricultural regions of the United States, damaging crops and soils. Subsurface tile…
Abstract
Purpose
Climate change is expected to cause larger and more frequent precipitation events in key agricultural regions of the United States, damaging crops and soils. Subsurface tile drainage is an important technology for mitigating the risks of a wetter climate in crop production. In this study, the authors examine how quickly farmers adapt to increased precipitation by investing in drainage technology.
Design/methodology/approach
Using farm-level data from the 2018 Agricultural Resource Management Survey (ARMS) of soybean producers, the authors construct a drainage adoption timeline based on when the operator began farming their land and when tile drainage was installed, if at all. The authors examine both the initial investment decision and the speed with which drainage is installed by adopters. A Heckman-style Poisson regression is used to model the count nature of adoption speed (measured in years taken to install tile drainage) and to correct for potential sample-selection bias.
Findings
The authors find that local precipitation is not a significant determinant of the drainage investment decision but may be highly influential in the timing of adoption among drainage users. Farms exposed to crop-damaging levels of precipitation install tile drainage faster than those with low to moderate levels of rainfall. Estimates of farm adaptation speeds are heterogeneous across farm and operator characteristics, most notably land tenure status.
Originality/value
Understanding how US farmers adapt to extreme weather through technology adoption is key to predicting the long-term impacts of climate change on America's food system. This study extends the existing climate adaptation literature by focusing on the speed of adoption of an important and increasingly common climate-mitigating technology – subsurface tile drainage.
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