Sezer Bozkus Kahyaoglu and Hakan Kahyaoglu
Introduction: In this study, approaches based on right-tail unit root tests are used to analyze high-frequency time series. Although these approaches successfully capture…
Abstract
Introduction: In this study, approaches based on right-tail unit root tests are used to analyze high-frequency time series. Although these approaches successfully capture unusually extreme price movements (bubbles) in financial markets, they can be biased in policymaking and forecasting. Testing the parameter stability enables the detection of both unusual price behavior and possible change points within the framework of the volatility approach. The break dates that cause the parameter change on the return series can be obtained, and the differentiation in the period can be seen.
Purpose: In this study, the analysis of periods that differ from the “changing parameter values” of the volatility process that emerged after November 2018 in the Borsa Istanbul (BIST) is made by using a new econometric approach in terms of change dates, parameter stability, and explosiveness characteristics. In this way, starting from determining periods with stable parameter values, the volatility process is tested to decide whether or not it shows an explosive feature.
Methodology: This study’s mainstay was published in February 2023. The findings reached within the framework of the knowledge provided by the technique in question will be the first in the applied literature. We used a uniform test for a mildly explosive GARCH process with double supreme statistics for BIST.
Findings: BIST is significantly affected by social and political events. This result implies that the “semi-efficient” market hypothesis for BIST needs to be re-examined in this context.
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Hongna Tian, Jingge Han, Meiling Sun and Xichen Lv
Toward sustainable development, radical green innovation (RGI) is necessary. Despite extensive research on the factors influencing green innovation, few studies have been…
Abstract
Purpose
Toward sustainable development, radical green innovation (RGI) is necessary. Despite extensive research on the factors influencing green innovation, few studies have been conducted on the precursors. Based on upper echelons (UE) theory, dynamic capability (DC) theory, “stimulus-organism-response” (SOR) theory, social information processing (SIP) theory and cognitive appraisal (CA) theory of emotion, the study explores how digital leadership (DL) affects RGI and investigates the mediating effects of green organizational identity (GOI) and the moderating effects of digital threat (DT) and technology for social good (TSG), as well as the multiple concurrent causalities that trigger high RGI.
Design/methodology/approach
The method of combining structural equation model (SEM) and fuzzy-set qualitative comparative analysis (fs QCA) is adopted in the study. Data from 233 questionnaires were collected at two different time points.
Findings
This study's findings indicate that the four dimensions of DL can positively influence RGI and GOI partially mediates between the four dimensions of DL and RGI. DT has a negative moderating effect between DL and GOI, while TSG is positively regulated between them, DT and TSG linkage moderates the partial mediating effect of GOI in DL and RGI. Further, fs QCA is used to analyze the causal complexity of DL dimensions and GOI to RGI and nine effective configuration paths are identified. It is found that the synergy of digital thinking ability (DTA), digital detection ability (DDA), digital social ability (DSA), digital reserve ability (DRA) and GOI is crucial to high RGI. Among them, GOI core appears the most times, indicating that GOI plays a vital role in improving enterprise RGI.
Originality/value
This study expands the literature on leadership and innovation by constructing a framework of “DL-GOI-RGI” and exploring the transmission of GOI and the boundary effect of DT and TSG. The study used fs QCA and SEM to better understand the statistical associations and the set relations between the conjunctions and conditions.
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Sumanjeet Singh, Dhani Shanker Chaubey, Rohit Raj, Vimal Kumar, Minakshi Paliwal and Seema Mahlawat
This study explores the intricate relationship between social media communication, consumer attitude and purchase intention within the context of lifestyle category products. With…
Abstract
Purpose
This study explores the intricate relationship between social media communication, consumer attitude and purchase intention within the context of lifestyle category products. With the rapid proliferation of social media platforms, businesses have turned to these platforms to connect with consumers and influence their purchasing decisions. This study aims to provide an in-depth analysis of how social media communication strategies impact consumer attitudes and, in turn, influence purchase intentions.
Design/methodology/approach
The study employs partial least squares structural equation modeling (PLS-SEM) to analyze the data collected from a sample of consumers.
Findings
The results of this study present that lack of visibility (LV), low-efficiency levels (LEL) and unpredictable elements (UE) are ranked as the top three major risk hurdles whereas real-time information on a package’s location (LV1), putting a GPS tracking system to track last-mile journey (OT3) and users wants on time location of their package (LV2) are ranked as top three most significant criteria affecting the practices of modern last-mile logistics in e-commerce businesses.
Research limitations/implications
The results of this study contribute to our understanding of how social media influences consumer behavior in the lifestyle product sector, shedding light on the underlying mechanisms that drive consumer purchasing decisions.
Originality/value
By constructing and testing experimentally a research model that reveals a thorough analysis of pertinent literature and identifies multiple important elements influencing consumer behavior in the lifestyle category, this paper adds to the body of knowledge on marketing. Practical ramifications for lifestyle firms are examined, along with suggestions for improving their social media tactics, in light of the findings.
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Gelvin Goestiawan and Njo Anastasia
The construction of homes to meet the primary needs of society results in a surge of harmful gas emissions into the ecosystem. Globally, the construction sector alone contributes…
Abstract
Purpose
The construction of homes to meet the primary needs of society results in a surge of harmful gas emissions into the ecosystem. Globally, the construction sector alone contributes a staggering 39% of gas emissions, underscoring the urgent need for green innovation to mitigate their adverse impacts. The concept of green living emerges as a strategy to address this challenge. Consequently, this research aims to delve into the influence of green brand positioning and perceived financial risk on the purchase intention of green residential properties, with attitude toward environment as a mediating variable.
Design/methodology/approach
This study adopts a quantitative associative approach, employing a purposive sampling technique to target consumers aged at least 21 years old who live in Indonesia. Data are collected through online questionnaires distributed via Google Forms, garnering responses from 269 participants. Data are processed using PLS-SEM with the SmartPLS 3.0 program for hypothesis testing.
Findings
The research findings reveal that both functional and emotional positioning have a significant impact on attitudes toward environmental concerns. However, green positioning does not exhibit such influence on these attitudes. Moreover, attitude toward environmental issues significantly affects purchase intentions, although perceived financial risk does not. This study also intimates that functional and emotional positioning significantly influence purchase intention, with attitude toward environment as a mediating variable.
Practical implications
Consumer priorities lie in the functional and emotional attributes of the green homes they purchase, while environmental consciousness needs to be heightened. However, investing in green living often entails bearing higher costs, thus creating financial constraints on consumers. This condition also calls for ongoing education and advocacy initiatives to bolster consumer awareness of green living practices, fostering consumer environmental awareness and active participation in efforts to reduce greenhouse gas emissions.
Originality/value
Research on green living remains limited in Indonesia due to insufficient understanding and low environmental awareness. It is imperative to address this issue to foster a deeper understanding of green concepts and promote environmentally conscious behavior on a wider scale.
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This study aims to investigate issues of natural resource management (NRM), conservation and ecotourism leadership on rural livelihood in Musina Local Municipality, Limpopo…
Abstract
Purpose
This study aims to investigate issues of natural resource management (NRM), conservation and ecotourism leadership on rural livelihood in Musina Local Municipality, Limpopo Province, South Africa. It concentrated on the existing and probable effects of ecotourism and integrated rural activities and their environmental influences on climate change and vice versa, subsistence and sustainability. The study utilizes a broad literature review, focus group discussions and field observations to investigate the municipality’s biodiversity, holistic livelihoods and tourism resource and facility concerns with climate change implications in the study area, with data analyzed manually and also by means of cross tabulations and central tendencies. A harmful link between ecotourism-induced environmental impacts and integrated rural activities that retain potential climate change consequences is found to exist in the vicinity. Nevertheless, it is fathomed in line with the study findings that when tourism actions adhere to the justifications of sustainable and responsible tourism management, they can result in better ecotourism products that foster environmental sustainability and enhance rural livelihoods. Therefore, the study has identified a need for decent ecotourism facilities and activities and a managerial approach to diminish climate change hazards and spur subsistence for local communities in the municipality. Within its rationale and ability, the study presents an analysis of conservation, ecotourism management, environmental degradation and responsible tourism qualities regarding climate change consequences within the municipality.
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Federico Bertacchini, Gianluca Gabrielli, Ennio Lugli and Pier Luigi Marchini
This study aims to identify the principal changes that digitalization has brought about in the internal audit functions (IAFs), focusing on the main characteristics that have been…
Abstract
Purpose
This study aims to identify the principal changes that digitalization has brought about in the internal audit functions (IAFs), focusing on the main characteristics that have been affected by this phenomenon.
Design/methodology/approach
The study follows a qualitative approach, involving the thematic analysis of semistructured interviews. A total of 22 professionals working in Italian-listed companies’ IAFs were interviewed. The framework of institutional theory was used to analyze the results.
Findings
The elements most affected by the digitalization of IAFs in Italy are: the skills required in IAFs, the relationship with external consultants and the types of activities performed by internal auditors (IArs). Nevertheless, the extent of the level digitalization within the IAFs of the companies analyzed appears to vary in accordance with the level of institutional pressures experienced by the organizations.
Originality/value
The study contributes to the literature on IA and digitalization by delineating the principal elements that are influenced by the digitalization process of IA. Moreover, it highlights how these elements develop and evolve as the level of digitalization of the IAF changes.
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Akash Deep Oraon, Swagota Saikia and Manoj Kumar Verma
Internet gaming disorder (IGD) has become a crucial concern due to its rising prevalence and potential mental health impacts, which can lead to significant psychological, social…
Abstract
Purpose
Internet gaming disorder (IGD) has become a crucial concern due to its rising prevalence and potential mental health impacts, which can lead to significant psychological, social and functional impairments, affecting academic performance, relationships and overall well-being of an individual. This paper aims to evaluate the published literature on IGD, identifying its growth, prolific authors, journals, countries, collaboration patterns and emerging research hotspots.
Design/methodology/approach
The present study has used scientometrics and altmetrics approaches to evaluate the published IGD literature. The data was collected from the Scopus database using the keywords TITLE-ABS-KEY, “Internet Gaming Disorder” or “Gaming Addiction” by filtering the period of 2014–2023, “research articles” and “English” language. Dimensions.ai has been used to extract the altmetric attention score. The results showed a total of 1,454 documents. The analysis has been done using VoSviewer and MS Excel.
Findings
The results showed an upward trend in publications over time. Dr Mark Griffiths is the most productive author, and the Journal of Behavioral Addictions is prolific. China is the most productive country. The study found minimal collaboration between the authors. The results highlighted that IGD predominantly affects adolescent males, leading to anxiety and significant impacts on brain function.
Originality/value
To the best of the authors’ knowledge, studies examining IGD research using both scientometric and altmetric approaches within the specified time frame have yet to be identified.
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Xumei Lin, Peng Wang, Shiyuan Wang and Jiahui Shen
The purpose of this paper is to investigate the accurate monitoring and assessment of steel bar corrosion in concrete based on deep learning multi-sensor information fusion…
Abstract
Purpose
The purpose of this paper is to investigate the accurate monitoring and assessment of steel bar corrosion in concrete based on deep learning multi-sensor information fusion method. The paper addresses the issue of traditional corrosion assessment models relying on sufficient data volume and low evaluation accuracy under small sample conditions.
Design/methodology/approach
A multi-sensor integrated corrosion monitoring equipment for reinforced concrete is designed to detect corrosion parameters such as corrosion potential, current, impedance, electromagnetic signal and steel bar stress, as well as environmental parameters such as internal temperature, humidity and chloride ion concentration of concrete. To overcome the small amount of monitoring data and improve the accuracy of evaluation, an improved Siamese neural network based on the attention mechanism and multi-loss fusion function is proposed to establish a corrosion evaluation model suitable for small sample data.
Findings
The corrosion assessment model has an accuracy of 98.41%, which is 20% more accurate than traditional models.
Practical implications
Timely maintenance of buildings according to corrosion evaluation results can improve maintenance efficiency and reduce maintenance costs, which is of great significance to ensure structural safety.
Originality/value
The corrosion monitoring equipment for reinforced concrete designed in this paper can realize the whole process of monitoring inside the concrete. The proposed corrosion evaluation model for reinforced concrete based on Siamese neural network has high accuracy and can provide a more accurate assessment model for structural health testing.
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Ahmed Oudah Mohammed Al-Dulaimi and Mohammed Abd-Al Wahab Mohammed
This paper aims to assume the responsibility of examining the shifting patterns of legal liability for failures that result from the integration of artificial intelligence (AI) in…
Abstract
Purpose
This paper aims to assume the responsibility of examining the shifting patterns of legal liability for failures that result from the integration of artificial intelligence (AI) in the public domain. It explores aspects such as the current legal implications, accountability mechanisms of AI errors and potential concerns and issues and proffered solutions for the complex issues that surround AI-related mistakes in public administration. Toward this end, the study outlines a central problem that is defined by the complex nature of errors that arise when AI is applied within the public service.
Design/methodology/approach
AI systems have recently been implemented into the public sectors and have influenced positive changes in efficiency and decision-making. However, the development and complication of AI technologies have raised profound worries on accountability in the case of mistakes in public sector.
Findings
As international governments increasingly rely on AI for critical selection and planning processes, establishing a clean prison system to educate and allocate responsibility when errors occur is paramount. What it has been found to have the potential to guide policy makers, criminologists and AI planners toward the challenges of implementing AI in the public sector easy to navigate. Finally, the research seeks to assess the potential of AI in public administration and will also serve to create a certain level of transparency, accountability and public trust.
Research limitations/implications
To provide a comprehensive response, the research employs a multifaceted methodology that encompasses a thorough literature review, in-depth legal analysis, regulatory assessment, exploration of various liability models, consideration of challenges and ethical considerations and real-world case studies. This holistic approach aims to shed light on the intricate web of legal responsibility and accountability entwined with AI in the public sector.
Practical implications
Although as a tool, AI is different from the human agents who use it, and defining and attributing legal responsibility for such errors becomes a challenging task because of the classification of AI as either software or a tool, and the accountability of its human users.
Social implications
Consequently, the primary research question emerges: “‘Employing’ AI in the public sector: how can legal responsibility for errors be assigned and governed in ways that respond to the plural employment-aspects of AI?”
Originality/value
The significance of this research lies in its ability to address the emerging challenges associated with AI adoption in the public sector. As international governments increasingly rely on AI for critical selection and planning processes, establishing a clean prison system to educate and allocate responsibility when errors occur is paramount. What it has been found to have the potential to guide policy makers, criminologists and AI planners toward the challenges of implementing AI in the public sector.
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Francisco Velasco-Morente, Vanessa Berbegal-Zaragoza and Sumita Srivastava
This study seeks to improve the understanding of the motivation driving the entrepreneurs of micro, small and medium enterprises (MSMEs) to integrate ICTs and why this process is…
Abstract
Purpose
This study seeks to improve the understanding of the motivation driving the entrepreneurs of micro, small and medium enterprises (MSMEs) to integrate ICTs and why this process is easier for some. The unified theory of acceptance and use of technology (UTAUT) is a suitable framework for this analysis. Our research aims to establish an explanatory typology based on the optimization of individual perceptions of entrepreneurs and usage intentions which enables identification of those groups that possess a greater intention to use ICTs in their businesses. This sheds light on how these factors influence their information and communication technology (ICT) adoption intentions within their businesses.
Design/methodology/approach
This study adopts an alternative approach and methodology to contribute new insights into academic discourse regarding the Unified Theory of Acceptance and Use of Technology (UTAUT). Building upon the theoretical foundation of the UTAUT, the present study pioneers the application of Data Envelopment Analysis (DEA) to a dataset encompassing 436 Spanish entrepreneurs. The objective is to examine the combination of diverse UTAUT perceptions that optimise the intention to implement ICTs in their companies while minimising anxiety associated with the adoption of new technologies (the outputs). Based on the results obtained, an explanatory typology is established that combines perceptions and usage intentions.
Findings
When applied to our group of entrepreneurs, DEA reveals that certain individuals can optimise their intentions with their current perception levels. This discovery has enabled us to create an explanatory typology through an examination of the efficiency of various perception-intention and/or anxiety combinations. Our proposed typology aims to shed light on the debate as to why not all perceptions translate into intentions and why certain entrepreneurs have a greater intention to use ICTs. An investigation of these efficient entrepreneurs reveals a wide range of combinations, which encompasses both those in harmony with effective usage behaviour and those deviating from such behaviour.
Research limitations/implications
DEA provides a snapshot of efficiency at a specific point in time and does not account for dynamic changes or adjustments over time, and DEA efficiency scores are relative measures that depend on the efficiency of other decision-making units in the dataset. The identification of appropriate benchmark units for comparison can be challenging, especially in heterogeneous datasets and cross-cultural analysis. In this respect, the UTAUT literature is lacking in cross-technology and cross-cultural comparisons.
Practical implications
Our methodology and results have implications for business management, business accelerators and economic policy. A detailed study of these clusters could reveal potential barriers and obstacles hindering the effective implementation of ICTs in MSMEs, thereby enabling researchers to focus on individuals who do not align with the model. Entrepreneurs classified in the most unfavourable typologies can take steps to enhance their perceptions, while administration and business accelerators can focus their efforts on these entrepreneurs.
Originality/value
The application of the UTAUT model on individual entrepreneurs receives limited coverage in the existing literature. To the best of our knowledge, this is the first study to utilise a DEA methodology within the framework of the UTAUT model (in contrast to the prevalent use of structural equation modelling in previous studies related to UTAUT). This analysis contributes fresh empirical evidence to the academic discourse on technology adoption models among individual entrepreneurs. Our methodology is a tool that reveals potential barriers and obstacles in individual perceptions that hinder the effective implementation of ICT in certain types of entrepreneurs.