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The empirical studies of the options market efficiency have reported contradictory results, which sometimes confuse practitioners and academicians. The aim of this study was to clarify several aspects of options market efficiency by exploring the answers to two main questions: Under what conditions is the options market more efficient? Are the discrepancies in the estimated efficiency due to the reality of efficiency or mismeasurement?

Using a meta-analysis approach, 54 studies have been analyzed, which included 1,315 tests. The sum of the observations for all of the tests is 3.7 m observation sets. The effect size (type r) has been used to compare the different statistics in different studies. The cumulative effect size and its diversification have been calculated by the random effects model and Q statistic, respectively.

The most interesting finding of the study was that the options market, in all circumstances, is significantly inefficient. Another important finding was that the heterogeneity of options market efficiency is due to the complexity of pricing relations, test time, violation index and price type. To overcome this heterogeneity and accuracy, future studies should test the no-arbitrage options pricing relations at different times and by different price types, using complex and simple pricing relations and either mean violation or violation ratio efficiency measures.

Public disagreement about the options market efficiency in past studies means that this variable is heterogeneous in different conditions. As a significant contribution, this study develops the literature by proposing the causes of options market efficiency heterogeneity.

We present an approach for pricing American put options with a regime-switching volatility. Our method reveals that the option price can be expressed as the sum of two components: the price of a European put option and the premium associated with the early exercise privilege. Our analysis demonstrates that, under these conditions, the perpetual put option consistently commands a higher price during periods of high volatility compared to those of low volatility. Moreover, we establish that the optimal exercise boundary is lower in high-volatility regimes than in low-volatility regimes. Additionally, we develop an analytical framework to describe American puts with an Erlang-distributed random-time horizon, which allows us to propose a numerical technique for approximating the value of American puts with finite expiry. We also show that a combined approach involving randomization and Richardson extrapolation can be a robust numerical algorithm for estimating American put prices with finite expiry.

Financial mathematics is one of the most rapidly evolving fields in today’s banking and cooperative industries. In the current study, a new fractional differentiation operator with a nonsingular kernel based on the Robotnov fractional exponential function (RFEF) is considered for the Black–Scholes model, which is the most important model in finance. For simulations, homotopy perturbation and the Laplace transform are used and the obtained solutions are expressed in terms of the generalized Mittag-Leffler function (MLF).

The homotopy perturbation method (HPM) with the help of the Laplace transform is presented here to check the behaviours of the solutions of the Black–Scholes model. HPM is well known for its accuracy and simplicity.

In this attempt, the exact solutions to a famous financial market problem, namely, the BS option pricing model, are obtained using homotopy perturbation and the LT method, where the fractional derivative is taken in a new YAC sense. We obtained solutions for each financial market problem in terms of the generalized Mittag-Leffler function.

The Black–Scholes model is presented using a new kind of operator, the Yang-Abdel-Aty-Cattani (YAC) operator. That is a new concept. The revised model is solved using a well-known semi-analytic technique, the homotopy perturbation method (HPM), with the help of the Laplace transform. Also, the obtained solutions are compared with the exact solutions to prove the effectiveness of the proposed work. The different characteristics of the solutions are investigated for different values of fractional-order derivatives.

This paper aims to examine the conditions under which small and medium enterprises (SMEs) invest in security services when they migrate their e-commerce applications to the cloud environment. Using a risk management perspective, the paper assesses the impact of security service pricing, security incident prevalence and virulence to estimate SME security spending at the market level and draw out implications for SMEs and security service providers.

Security risks are inherently characterized by uncertainty. This study uses a Monte Carlo approach to understand the role of uncertainty in the decision to adopt security services. A model relating key security constructs is assembled based on key constructs from the domain. By manipulating security service costs and security incident types, the model estimates the market-level adoption of services, security incidents and damages incurred, along with measures of their relative dispersion.

Three key findings emerge from this study. First, adoption of services and protection is higher when tiered security services are provided, indicating that SMEs prefer to choose their security services rather than accept uniformly priced products. Second, SMEs are considered price-sensitive, resulting in a maximum level of spending in the market. Third, results indicate that security incidents and damages can be much higher than the mean in some cases, and this should serve as a cautionary note to SMEs.

Security spending has been modeled at the firm level. Adopting a market-level perspective represents a novel contribution. Additionally, the Monte Carlo approach provides managers with tangible measures of uncertainty, affording additional information and insight when making security service adoption decisions.

This study investigates the influence of e-marketing risks on a Corporation’s Reputation (CR) resulting from its online marketing of products and services.

A comprehensive analysis was conducted to enhance the company’s e-marketing strategies and bolster its reputation in the market. This involved an investigation into key factors of e-marketing risks, such as customer confidence, product quality, marketing fraud, credibility and customer knowledge and proficiency in using online platforms. These factors have directly impacted the company’s reputation, including aspects such as product/service quality, attractiveness, performance and commitment to social responsibility.

Its finding indicates that customers' lack of confidence in e-marketing has a strong impact on CR, followed by product quality and credibility. The absence of consumer awareness about e-marketing websites and e-fraud frequently negatively affects the organizational reputation.

To enhance the corporation’s reputation, it is recommended that companies provide educational resources on online shopping, including guidance on using the company’s website, comparing prices and other services that facilitate online purchases. This will help to support the credibility of e-marketing and enhance customer trust.

This research is an exploration of how e-marketing has affected a Corporation’s Reputation. It provides modern knowledge about the dynamic interplay between digital strategies and brand perception. Investigating this relationship provides valuable insights into the evolving landscape of consumer trust in the digital age. By analysing the various ways in which e-marketing influences a company’s reputation, innovative approaches can be developed to enhance its online presence and build lasting customer trust.

This study aims to investigate the impact of housing knowledge, housing challenges and housing policy on the renting intention and satisfaction of young people.

A questionnaire survey helped collect data from young people in the study area, which were then analysed using the Statistical Package for the Social Sciences (SPSS) 27 software. A descriptive analysis and the Cronbach’s alpha test were adopted to analyse the data. The confirmatory factor analysis confirmed a significant relationship between housing knowledge, housing challenges and housing policy and renting intention and satisfaction.

The overall findings revealed that most young people intend to own a home one day, and a minority of them decided to continue renting. The findings suggest that there is a significant relationship between housing knowledge and housing intention. However, housing challenges and housing policies do not appear to impact renting intentions. On the other hand, housing knowledge and housing challenges were found to be associated with housing satisfaction, while housing policy does not show a significant relationship.

This study, however, poses limitations as it uses a limited model and location and involves only a cross-sectional study. Future studies can use the methodology used in this study to conduct further investigations on housing intention and satisfaction in other regions of the country, thereby validating the findings of this study.

In terms of practical implications, this study has made a valuable contribution to the field of housing literature by shedding light on two crucial elements, namely, housing intention and satisfaction, which have been understudied. Understanding the determinants of housing intention and satisfaction is vital in efforts to implement appropriate policy reforms.

Findings from this study offer valuable insight related to managerial and practical implications, with the former implicating a need to prioritise initiatives that enhance renters’ housing knowledge. Implementing educational programmes and providing accessible resources can empower renters with a better understanding of the rental process and other important housing information.

This paper is relevant because it provides a guideline for policymakers to initiate regulations concerning housing and implement appropriate policy reforms. This study can also help housing providers develop more affordable housing that meets the needs of young people currently renting because most have expressed their housing intentions. Understanding housing intention and satisfaction determinants is vital to implementing appropriate policy reforms.

This study aims to validate the link between production manipulation and a firm’s performance variability (fundamentals and stock returns). It explores whether executives' risk-taking incentives encourage production deviations around the normal level during uncertainty.

Utilizing panel data of manufacturing firms from Compustat over three decades, the study investigates production management practices during economic uncertainty. The Economic Policy Uncertainty Index (EPU) is employed as a key metric. The empirical strategy involves documenting the effect of economic uncertainty on overproduction and underproduction, examining the role of executive compensation and assessing the impact on risk.

The research finds that risk-taking incentives increase over/underproduction, particularly amplifying the extent of underproduction during uncertainty. Production deviation rises, indicating that firms take greater risk by engaging in abnormal business operations. The study’s results are robust against various econometric methods, emphasizing the influence of risk-taking incentives on corporate production decisions.

While providing valuable insights, the study acknowledges inherent limitations, including factors influencing production decisions beyond risk-taking incentives. Further research could explore additional determinants for a comprehensive understanding.

The findings highlight the potential dark side of executive compensation that motivates suboptimal risk-taking decisions, impacting risk, cost of capital and firm performance. Policymakers and compensation committees can use these insights to design efficient systems that mitigate moral hazard problems associated with productivity changes.

The study emphasizes the broader social implications of production manipulation under uncertainty. It prompts discussions on the ethical considerations of managerial opportunism, its potential consequences for stakeholders and market dynamics.

This study contributes to the literature by examining the role of economic uncertainty on production manipulation and the influence of risk-taking incentives. It extends the earnings management literature by considering real activity manipulation and emphasizing the importance of decomposing production deviation into positive and negative values.

This study aims to reveal the food preferences and to define the typology of digital nomads as gastro-tourists. In this context, it is aimed to provide information on issues such as the importance of food culture in destination selection for digital nomads, food prices, local dishes, local food markets, religious restrictions, researching cultural cuisines, preparing meals and participating in gastronomic events.

Multiple qualitative methods were utilized in the research for this study. Digital nomads' comments, videos and semi-structured interviews constitute the data sources of the research, and the data obtained were analyzed by content analysis.

As a result of the study, it was seen that digital nomads do consider gastronomy in their destination selection, and five different gastro-tourist profiles were determined. These are Local Flavor Hunters, Gastronomy Adventurers, Budget-Conscious Food Lovers, Cultural Explorers and Health and Sustainability Focused People.

The theoretical contribution of the study is to provide information with regard to the food and beverage preferences of digital nomads and to contribute to filling a gap in the literature. The practical contribution of the study is to help formulate tourism marketing strategies in the destination and strategies for businesses in the tourism industry. Since digital nomads play important roles in destination promotion, it is important to determine their perspectives and typologies towards gastronomy. The results of the study will be useful for tourism industry components, such as academics, experts, travel businesses, tourism destinations and local food producers who research the tourism industry and travel trends.

This study aims to examine the interaction effects of chatbots’ language style and customers’ decision-making journey stage on customer’s service encounter satisfaction and the mediating role of customer perception of emotional support and informational support using the construal level theory and social support theory as conceptual frameworks.

This study used a scenario-based experiment with a 2 (chatbot’s language style: abstract language vs concrete language) × 2 (decision-making journey stage: informational stage vs transactional stage) between-subjects design.

Findings show that during the informational stage, chatbots that use abstract language style exert a strong influence on service encounter satisfaction through emotional support. During the transactional stage, chatbots that use concrete language style exert a strong impact on service encounter satisfaction through informational support.

Findings provide some suggestions for improving customer–chatbot interaction quality during online service encounters.

This study offers a novel perspective on customer interaction experience with chatbots by investigating the chatbot’s language styles at different decision-making journey stages.

Pune is a prominent information technology (IT) hub in India, where snacking has become a customary practice among IT professionals. This study aims to determine the pattern and factors associated with snacking among IT professionals from various multinational corporations (MNCs) in Pune, Maharashtra, India.

This cross-sectional study considered 404 IT professionals aged 21 to 50 years. A convenient sampling method was adopted to administer a validated questionnaire. Information on snacking patterns and factors associated with snacking were recorded. Descriptive and inferential statistics were used to analyze the data with p = 0.05. The participation was voluntary, and confidentiality was ensured.

The mean age of the participants was 31 ± 7.9 years. Almost half (51.5%) of the participants engaged in daily snacking. The sociodemographic factors such as younger age (0.000), marital status (p = 0.001), salary package (p = 0.006), living situation (p = 0.05), designation (p = 0.042) and work experience (p = 0.001) significantly related with the unhealthy snacking pattern scores. Daily snacking was significantly associated with hunger (p = 0.001), stress (p = 0.001), weight (p = 0.000), peer influence (p = 0.041) and taste (p = 0.001). Hunger, stress, taste, peer influence, boredom and weight were significantly (p = 0.05) associated with unhealthy snacking patterns.

The mean age of the participants was 31 ± 7.9 years. Almost half (51.5%) of the participants engaged in daily snacking. The sociodemographic factors such as younger age (0.000), marital status (p = 0.001), salary package (p = 0.006), living situation (p = 0.05), designation (p = 0.042) and work experience (p = 0.001) significantly related with the unhealthy snacking pattern scores. Daily snacking was significantly associated with hunger (p = 0.001), stress (p = 0.001), weight (p = 0.000), peer influence (p = 0.041) and taste (p = 0.001). Overall, hunger, stress, taste, peer influence, boredom and weight were significantly (p = 0.05) associated with unhealthy snacking patterns such as snacking in between, prioritizing taste over nutrition, exclusion of fruits and vegetables in snacks, lack of control over snacking and snacking habit.

This study uniquely identifies the snacking pattern of IT professionals from Pune, India, which primarily includes unhealthy snacking. Various socio-demographic and other factors such as hunger, taste, stress, boredom, convenience, weight and peer influence, were associated with unhealthy snacking. Understanding the snacking pattern and its determinants can help create nutrition interventions to promote healthy snacking and decrease the risk of noncommunicable diseases in IT professionals.