Search results
1 – 10 of over 1000Parvathy S. Nair and Atul Shiva
The study explored various dimensions of overconfidence bias (OB) among retail investors in Indian financial markets. Further, these dimensions were validated through formative…
Abstract
Purpose
The study explored various dimensions of overconfidence bias (OB) among retail investors in Indian financial markets. Further, these dimensions were validated through formative assessments for OB.
Design/methodology/approach
The study applied exploratory factor analysis (EFA) to 764 respondents to explore dimensions of OB. These were validated with formative assessments on 489 respondents by the partial least square path modeling (PLS-PM) approach in SmartPLS 4.0 software.
Findings
The major findings of EFA explored four dimensions for OB, i.e. accuracy, perceived control, positive illusions and past investment success. The formative assessments revealed that positive illusions followed by past investment success among retail investors played an instrumental role in orchestrating the OBs that affect investment decisions in financial markets.
Practical implications
The formative index of OB has several practical implications for registered financial and investment advisors, bank advisors, business media companies and portfolio managers, besides individual investors in the domain of behavioral finance.
Originality/value
This research provides a novel approach to provide a formative index of OB with four dimensions. This formative index can acts as an overview for upcoming researchers to investigate the OB of retail individual investors.
Highlights
Overconfidence bias is an important predictor of retail investors' behavior
Formative dimensions of the overconfidence bias index.
Accuracy, perceived control, positive illusions and past investment success are important dimensions of overconfidence bias.
Modern portfolio theory and illusion of control theory support this study.
Overconfidence bias is an important predictor of retail investors' behavior
Formative dimensions of the overconfidence bias index.
Accuracy, perceived control, positive illusions and past investment success are important dimensions of overconfidence bias.
Modern portfolio theory and illusion of control theory support this study.
Details
Keywords
Since the past two years, workplace dynamics has changed, as employees have witnessed uncertainty and a constantly fluctuating business environment due to COVID-19. The outbreak…
Abstract
Purpose
Since the past two years, workplace dynamics has changed, as employees have witnessed uncertainty and a constantly fluctuating business environment due to COVID-19. The outbreak is nearly over, but it has led to new work settings in most parts of the world. This requires a suitable leadership approach to derive strategic decisions and cultivate proficiency amongst employees in the new work setting. The purpose of the article is to explore the effects of ambidextrous leadership (AL) in boosting social capital (SC) which further lead to employee creative work behavior. Further, the study also examined the moderating role of well-being in enriching creative work behavior.
Design/methodology/approach
In this study, 281 knowledge workers working in Mumbai were selected as subjects for the study. Structural equation modelling using analysis of moment structure was used to test the mediation. Later, moderated regression analysis confirmed the moderating role of well-being in employee creative behaviour.
Findings
The results confirmed the role of AL comprising closed and open leadership behaviours in enhancing the SC, which is an important element to cultivate creative behaviour amongst employees. In addition, the role of well-being is found to be critical for enhancing creative work behaviour.
Practical implications
The study will help organizations to understand the role of AL, SC and well-being in enhancing creative behaviour amongst knowledge workers.
Originality/value
This study contributes to leadership literature by attempting to integrate the concepts of leadership with SC, well-being and creative work behaviour, which has rarely been done in the Indian context.
Details
Keywords
Ping Li, Zhipeng Chang and Wenhe Chen
To maintain the bottom line of food import risk in China, this paper proposes a novel risk state evaluation model based on bottom-line thinking after analyzing the decision-making…
Abstract
Purpose
To maintain the bottom line of food import risk in China, this paper proposes a novel risk state evaluation model based on bottom-line thinking after analyzing the decision-making ideas embedded in the bottom-line thinking method.
Design/methodology/approach
First, the order relation analysis method (G1 method) and Laplacian score (LS) are applied to calculate the constant weights of indexes. Then, the worst-case scenario of food import risk can be estimated to strive for the best result, so the penalty state variable weight function is introduced to obtain variable weights of indexes. Finally, the study measures the risk state of China's food import from the overall situation using the set pair analysis (SPA) method and identifies the key factors affecting food import risk.
Findings
The risk states of food supply in eight countries are in the state of average potential and partial back potential as a whole. The results indicate that China's food import risks are at medium and upper-medium risk levels in most years, fluctuating slightly from 2010 to 2020. In addition, some factors are diagnosed as the primary control objects for holding the bottom line of food import risk in China, including food output level, food export capacity, bilateral relationship and political risk.
Originality/value
This paper proposes a novel risk state evaluation model following bottom-line thinking for food import risk in China. Besides, SPA is first applied to the risk evaluation of food import, expanding the application field of the SPA method.
Details
Keywords
This paper aims to help understand how adopting risk allocation criteria impacts the delivery of public–private partnership (PPP) mass housing in Nigeria with the view of…
Abstract
Purpose
This paper aims to help understand how adopting risk allocation criteria impacts the delivery of public–private partnership (PPP) mass housing in Nigeria with the view of promoting the adoption of PPP housing scheme in Nigeria.
Design/methodology/approach
The research design adopts the census sampling approach by using well-structured questionnaires distributed to stakeholders involved in PPP-procured mass housing projects, i.e. consultants, in-house professionals, contractors and the organized private sector, registered with PPP departments in the Federal Capital Territory Development Authority, Abuja, Nigeria. Sixty-three risk factors, nine risk allocation criteria and nine project delivery indices were submitted for the respondents to rank on a Likert scale of 7. Two hypotheses were formulated to test whether the risk allocation criteria impacted PPP mass housing delivery or otherwise. The study adopts partial least square-structural equation modeling to model the effect of risk on risk allocation criteria on project delivery indices and risk severity.
Findings
The finding shows that project risk allocation criteria have less effect on project delivery indices than on risk severity. The study concludes that risk allocation principles do not directly affect the delivery of PPP-procured mass housing projects. This is evident by the path coefficient of 0.724 values, which is not statistically significant at a 5% alpha protection value. The study concludes that allocating critical risk factors influences the performance of PPP-procured mass housing projects, as the path coefficient of 0.360 is also not significantly far from 0 and at a 5% alpha protection value.
Originality/value
The study is one of the recent studies conducted in PPP-procured mass housing projects in Nigeria owing to the novelty of procurement option in the sector. It highlights the risk factors that can jeopardize the PPP-procured mass housing project objectives. The study is of immense value to PPP actors in the sector by providing the necessary information required to formulate risk response methods to minimize the impact of the risk factors in PPP mass housing projects.
Details
Keywords
Veysel Yilmaz and Yelda Sürmeli̇oğlu
In this study, the service quality of an automobile authorized service center was investigated based on the European Customer Satisfaction Index (ECSI) model. The ECSI model…
Abstract
Purpose
In this study, the service quality of an automobile authorized service center was investigated based on the European Customer Satisfaction Index (ECSI) model. The ECSI model includes image, customer expectations, perceived quality, perceived value, customer satisfaction, customer complaints and customer loyalty.
Design/methodology/approach
In the study, an attempt was made to improve the ESCI model by adding the trust factor as a moderating variable. After an extensive literature review, measurement questions were developed to best represent the factors in the research model. Partial least squares structural equation modeling (PLS-SEM) was used to test the fit of the research model and test the hypotheses.
Findings
As a result of the analysis, only one of the 13 hypotheses tested was not supported. According to the results of hypothesis testing, the highest effect was found in the relationship between customer satisfaction customer complaints, customer expectations and perceived quality. In addition, customer expectations affect customer satisfaction indirectly rather than directly. In this case, customer expectations, perceived value and perceived quality influence customer satisfaction.
Practical implications
The customer satisfaction quality index score of the authorized automobile service whose service quality was measured was calculated as 72.75. Although customers were generally satisfied with the authorized service, their expectations were not fully met.
Originality/value
In the study, an attempt was made to improve the ECSI model by adding a trust factor. Trust, which was added to the model as a moderator variable, fit the model. As a result, it was revealed that trust has an increasing regulatory effect on the relationship between perceived quality and customer satisfaction.
Details
Keywords
Siqi Wang, Jun-Hwa Cheah, Chee Yew Wong and T. Ramayah
This study aims to evaluate the usage of partial least squares structural equation modeling (PLS-SEM) in journals related to logistics and supply chain management (LSCM).
Abstract
Purpose
This study aims to evaluate the usage of partial least squares structural equation modeling (PLS-SEM) in journals related to logistics and supply chain management (LSCM).
Design/methodology/approach
Based on a structured literature review approach, the authors reviewed 401 articles in the field of LSCM applying PLS-SEM published in 15 major journals between 2014 and 2022. The analysis focused on reasons for using PLS-SEM, measurement model and structural model evaluation criteria, advanced analysis techniques and reporting practices.
Findings
LSCM researchers sometimes did not clarify the reasons for using PLS-SEM, such as sample size, complex models and non-normal distributions. Additionally, most articles exhibit limited use of measurement models and structural model evaluation techniques, leading to inappropriate use of assessment criteria. Furthermore, progress in the practical implementation of advanced analysis techniques is slow, and there is a need for improved transparency in reporting analysis algorithms.
Originality/value
This study contributes to the field of LSCM by providing clear criteria and steps for using PLS-SEM, enriching the understanding and advancement of research methodologies in this field.
Details
Keywords
The identification of network user relationship in Fancircle contributes to quantifying the violence index of user text, mining the internal correlation of network behaviors among…
Abstract
Purpose
The identification of network user relationship in Fancircle contributes to quantifying the violence index of user text, mining the internal correlation of network behaviors among users, which provides necessary data support for the construction of knowledge graph.
Design/methodology/approach
A correlation identification method based on sentiment analysis (CRDM-SA) is put forward by extracting user semantic information, as well as introducing violent sentiment membership. To be specific, the topic of the implementation of topology mapping in the community can be obtained based on self-built field of violent sentiment dictionary (VSD) by extracting user text information. Afterward, the violence index of the user text is calculated to quantify the fuzzy sentiment representation between the user and the topic. Finally, the multi-granularity violence association rules mining of user text is realized by constructing violence fuzzy concept lattice.
Findings
It is helpful to reveal the internal relationship of online violence under complex network environment. In that case, the sentiment dependence of users can be characterized from a granular perspective.
Originality/value
The membership degree of violent sentiment into user relationship recognition in Fancircle community is introduced, and a text sentiment association recognition method based on VSD is proposed. By calculating the value of violent sentiment in the user text, the annotation of violent sentiment in the topic dimension of the text is achieved, and the partial order relation between fuzzy concepts of violence under the effective confidence threshold is utilized to obtain the association relation.
Details
Keywords
Kathrin Kölbl, Cornelia Blank, Wolfgang Schobersberger and Mike Peters
This study aims to address customer focus as an important component of total quality management (TQM) and explore the key drivers of member satisfaction in tennis clubs via a…
Abstract
Purpose
This study aims to address customer focus as an important component of total quality management (TQM) and explore the key drivers of member satisfaction in tennis clubs via a novel theory-based member satisfaction index (MSI) model with high explanatory and predictive power. Furthermore, the study aims to investigate the relationship between satisfaction and behavioral intentions (willingness to stay; WTS) with consideration of the mediating effect of identification with the club.
Design/methodology/approach
This study uses variance-based partial least squares structural equation modeling (PLS-SEM) to estimate the MSI model, which was tested in a leading tennis club in Germany (n = 185).
Findings
The results reveal that club atmosphere, club facilities and the price/quality ratio of the membership fee are the most important drivers of member satisfaction in tennis clubs. Member satisfaction has a large influence on the WTS of tennis club members. Identification with the club, when included as a mediator in the model, increases the variance explained in WTS considerably.
Research limitations/implications
The small sample limits the generalizability of findings, and further research is recommended.
Practical implications
The MSI model is a useful benchmark tool for club managers who want to quantify the satisfaction and WTS of their club members. In addition, because of the integrated formative measurement models, the PLS-SEM results show which indicators can be used to positively impact satisfaction with each of the service quality dimensions, overall member satisfaction and WTS. The most important of these results are discussed in an importance-performance map analysis.
Originality/value
The MSI model is a multi-attribute index model through which members' evaluations of various dimensions of service and value are derived through multivariable linear function with each dimension weighted according to its importance in one holistic model. The model shows the strong impact of satisfaction on WTS of sports club members and reveals that findings of previous research on the relationship between fan and spectator identification and loyalty are transferable to sports club members. The MSI represents a new contribution to the literature; it was applied here to tennis clubs but is also suitable for application to other sports clubs.
Details
Keywords
The purpose of the paper is to explore the economic repercussions of potential India–USA free trade agreement (FTA) on the trade of agricultural commodities at HS 2-digit level.
Abstract
Purpose
The purpose of the paper is to explore the economic repercussions of potential India–USA free trade agreement (FTA) on the trade of agricultural commodities at HS 2-digit level.
Design/methodology/approach
The analysis is undertaken by assuming tariff reduction in a phased manner using the World Integrated Trade Solutions (WITS)-SMART partial equilibrium model to identify the trade creation and trade diversion effects.
Findings
Overall results show that both the trading partners gain from the proposed FTA. Trade creation dominates over trade diversion in India's analysis.
Practical implications
An FTA between India and the USA could be an essential step toward more liberal trade regimes and provide enormous economic benefits to both countries. Government of both the countries should support deeper integration. This will create more job opportunities and generate prosperity in both economies.
Originality/value
There are numerous studies conducted on evaluating the impact of FTAs ratified between countries. But there are limited studies which evaluate the impact of the proposed India–USA FTA on the economies of both trading partners specifically on the agriculture sector.
Details
Keywords
The primary objective of this research is to provide evidence that there are two distinct layers of investor sentiments that can affect asset valuation models. The first is…
Abstract
Purpose
The primary objective of this research is to provide evidence that there are two distinct layers of investor sentiments that can affect asset valuation models. The first is general market-wide sentiments, while the second is biased approaches toward specific assets.
Design/methodology/approach
To achieve the goal, the authors conducted a multi-step analysis of stock returns and constructed complex sentiment indices that reflect the optimism or pessimism of stock market participants. The authors used panel regression with fixed effects and a sample of the US stock market to improve the explanatory power of the three-factor models.
Findings
The analysis showed that both market-level and stock-level sentiments have significant contributions, although they are not equal. The impact of stock-level sentiments is more profound than market-level sentiments, suggesting that neglecting the stock-level sentiment proxies in asset valuation models may lead to severe deficiencies.
Originality/value
In contrast to previous studies, the authors propose that investor sentiments should be measured using a multi-level factor approach rather than a single-factor approach. The authors identified two distinct levels of investor sentiment: general market-wide sentiments and individual stock-specific sentiments.
Details