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Drawing from the Personal Construct Theory, this study aims to analyze the impact of using gamified apps on user behavior by investigating the service-related images and individual preferences of Generation Z (GenZ) consumers, as these emerge from gamified applications in a tourism context.

The repertory grid analysis (RGA) elicited the top elements that reflect GenZer perceptions in tourism from empirical studies in the UK and Greece. Generalized procrustes analysis was used to investigate the structure of the data for the creation of representative consensus biplots of the most important conceptual constructs to advance consumer decision-making modeling via gamification.

As per different gamified app best-practices considered, the authors extract not only common perceptual elements (e.g. place informative aspects, exploration, lodgings, food/catering) but also different image components (e.g. virtual/interactive, business vs commercial traveling, entertainment, heritage/cultural informative aspects) from comparing UK with Greek GenZers’ responses. These extracted attributes are then presented in two dimensional charts, respectively, toward creating tourist perception scales.

Notwithstanding the wide availability of gamified apps, research on gamification design in tourism and hospitality is still in the early phase. This study demonstrates the need to identify and optimize the formation of different images among GenZers. It also highlights the advantageous nature of the proposed combination of procrustes analysis with the RGA.

To the best of the authors’ knowledge, this research is among the first empirical ones toward creating scales for measuring tourist perceptions of GenZers coming from different consumer markets. It responds to scholars’ recent calls for better informing gamification design and improving contemporary consumer experience.

Light field images (LFIs) have gained popularity as a technology to increase the field of view (FoV) of plenoptic cameras since they can capture information about light rays with a large FoV. Wide FoV causes light field (LF) data to increase rapidly, which restricts the use of LF imaging in image processing, visual analysis and user interface. Effective LFI coding methods become of paramount importance. This paper aims to eliminate more redundancy by exploring sparsity and correlation in the angular domain of LFIs, as well as mitigate the loss of perceptual quality of LFIs caused by encoding.

This work proposes a new efficient LF coding framework. On the coding side, a new sampling scheme and a hierarchical prediction structure are used to eliminate redundancy in the LFI's angular and spatial domains. At the decoding side, high-quality dense LF is reconstructed using a view synthesis method based on the residual channel attention network (RCAN).

In three different LF datasets, our proposed coding framework not only reduces the transmitted bit rate but also maintains a higher view quality than the current more advanced methods.

(1) A new sampling scheme is designed to synthesize high-quality LFIs while better ensuring LF angular domain sparsity. (2) To further eliminate redundancy in the spatial domain, new ranking schemes and hierarchical prediction structures are designed. (3) A synthetic network based on RCAN and a novel loss function is designed to mitigate the perceptual quality loss due to the coding process.

Defining and validating a map of related technologies is critical for managers, investors and inventors. Because of the increase in the applications of and demand for semiconductor lasers, analyzing the technological position of developers has become increasingly critical. Therefore, the purpose of this study is to adopt the technological position analysis to identify mainstream technologies and developments relevant to semiconductor lasers.

Correspondence analysis and k-means cluster analysis, which are data mining techniques, are used to reveal strategic groups of major competitors in the semiconductor laser market according to their Patent Cooperation Treaty (PCT) patent applications.

The results of this study reveal that PCT patent applications are generally obtained for masers, optical elements, semiconductor devices and methods for measuring and that technology developers have varying technological positions.

Through position analysis, this study identifies the technological focuses of different manufacturers to obtain information that can guide the allocation of research and development resources.

Based on Kansei Engineering, this study obtained consumers' emotional preferences aiming to enhance the emotional connection between consumers and clothing to extend the service life of clothing and realize sustainable clothing design.

Six Kansei word pairs that are the most important to consumers were identified through literature reviews, magazines, websites, card sorting of consumers and cluster analysis. Finally, the consumers scored the 32 product specimens through a 5-level rating semantic differential scale questionnaire of six Kansei word pairs. The researchers verified the consumers' emotional preferences through principal component analysis and established the relationship between Kansei words and design elements of color through partial least squares.

The study found consumers' emotional preferences: elegant, minimalist, formal, casual, mature, practical and distinctive style. Besides white, black, gray, blue, consumers will also like red and yellow-red in the future. The crucial findings of this study are to get recommended guidelines that consumers' emotional preferences match the corresponding design elements.

The study's findings can be used to style the design of men's plain-color shirts and guide online marketers and designers to design apparel that meets consumers' emotional needs to develop consumers' sustainability reliance on clothing. This study also explains the overall process and methodology for integrating consumer preferences and product design elements.

The purpose of this study was to determine whether there are differences in skin temperature under graphene-infused fleece and traditional polyester fleece materials in the interior of a wetsuit.

A total of 48 participants surfed for a minimum of 40 min in a custom wetsuit with a torso lined with graphene-infused fleece on one half and traditional polyester fleece on the other. Eight iButton thermistors were used to record skin temperatures bilaterally at the upper back, chest, abdomen and lower back every minute for the entire surf session. After surfing, participants responded to questions associated with their perception of warmth and comfort and their knowledge of fleece materials.

Skin temperatures did not differ between the two types of fleece at the upper back, chest and abdomen locations. Skin temperatures in the lower back were significantly warmer under the traditional polyester fleece compared to graphene-infused fleece. Participant responses associated with warmth were consistent with skin temperature measurements.

The results of this study indicate that a graphene-infused nylon fleece interior does not clearly influence skin temperature in surfers when compared to a traditional polyester fleece interior. While skin temperatures were significantly lower under the graphene-infused nylon fleece at the low back, the other three anatomical locations did not exhibit significant differences.

Thermoregulation is an important consideration for the safety and performance of surfers in the ocean. Evidence suggests that the inner lining of a wetsuit may impact thermoregulation while surfing; however, no prior studies have compared interior materials.

With the proliferation of ideas submitted by users in firm-built online user innovation communities, community managers are faced with the problem of user idea overload. The purpose of this paper is to explore the influencing factors on the idea adoption to identify high quality ideas, and then propose a method to quickly filter high value ideas.

The authors collected more than 110,000 data submitted by Xiaomi community users and analyzed the factors affecting idea adoption using a multinomial logistic regression model. In addition, the authors also used BP neural network to predict the idea adoption process.

The empirical results show that idea semantics, number of likes, number of comments, number of related posts, the existence of pictures and self-presentation have positive impact on idea adoption, while idea length and idea timeliness had negative impact on idea adoption. In addition, this paper calculates the idea evaluation value through the idea adoption process predicted by neural network and the mean value of idea term frequency inverse document frequency (TF-IDF).

This empirical study expands the theoretical perspective of idea adoption research by using dual-process theory and enriches the research methods in the field of idea adoption research through the multinomial logistic regression method. Based on our findings, firms can quickly identify valuable ideas and effectively alleviate the information overload problem of online user innovation communities.

Valuers should independently assess market value. The purpose of this article is to analyze whether the valuation behavior remains independent when commissioned by publicly listed companies in Taiwan.

This study used both quantitative and qualitative methods. Quantitative data analysis was used to examine the estimated premium ratio and estimated divergent ratio with the independent sample t test and Wilcoxon-Mann-Whitney test. To complement and validate the quantitative analysis, open-ended questionnaires were conducted, providing additional insights into the research findings.

The results showed that there is a significant difference in estimated valuations commissioned by representatives of buyers and sellers, and the estimated premium ratios commissioned by representatives of buyers were higher than those of sellers. Furthermore, the open-ended questionnaires results indicate that these findings may be influenced by clients for less experienced appraisers. However, for senior appraisers, this is seen as an action to gain a better understanding of the valuation purpose and always within a reasonable price range. In addition, client influence is not a static factor; it may transform into the valuer's behavior as the appraiser's experience grows and deepens.

It is difficult to obtain valuation reports commissioned by representatives of both buyers and sellers for the same property transactions. In this study, data were obtained from the Market Observation Post-System (MOPS) in Taiwan. As valuation reports could not be obtained, estimated valuations and transaction prices are used to calculate estimated premium ratio and estimated divergent ratios.

Previous investigations of the client effect have been conducted using qualitative methods including questionnaire surveys, in-depth interviews and experimental design. However, these studies are subject to moral hazard. This study may be the first study that has access to data on valuations for both buyers and sellers in such a formal setting.

This article aims to understand users' information needs in the metaverse communities and to analyze the similarities and differences between their information needs and those of users in Internet communities.

This study conducted semi-structured interviews with users in the metaverse communities to gather raw data. Grounded theory research methods were employed to code and analyze the collected interview data, resulting in the extraction of 40 initial concepts, 15 subcategories and 5 main categories. Based on Maslow’s hierarchy of needs theory, this paper constructs the hierarchical model of users' information needs in the metaverse communities. It compares the differences between users' information needs in the metaverse and Internet fields.

The user’s information needs in the metaverse communities are divided into two types: deficiency needs and growth needs. Deficiency needs have two levels. The first level is the demand for basic information resources. The second level is the users demand for information assistance. Growth needs have three levels. The first level is the need for information interactions. The second level is the need for community rules. The ownership information in the community rules can provide proof of user status, assets and so on. The third level is the need for users to contribute and share their own created information content.

This article presents the latest research data from in-depth interviews with users in the metaverse communities. It aims to help builders and managers of metaverse communities understand users' information needs and improve the design of virtual communities.

This study integrates previous research on the intention to use Airbnb to determine which antecedents provide a parsimonious explanation.

Meta-analyses based on 61 samples estimate how 8 antecedents are associated with the intention to use Airbnb. Subsequent analyses utilize meta-analyses to estimate a regression model to simultaneously estimate the relationship between the antecedents and the intention to use Airbnb. Relative weight analysis then determined each antecedent’s utility.

A parsimonious model with only four antecedents (hedonic motivation, price value, effort expectancy and social influence) was nearly as predictive as the full eight-antecedent model. Ten moderating variables were examined, but none were deemed to consistently influence the relationships between the antecedents and the intention to use Airbnb.

Relatively few measures (i.e. four) effectively explain customers’ intentions to use Airbnb. When these measures cannot be readily influenced, alternatives are also presented. Implications for the travel industry are considered and straightforward approaches to increasing users are presented.

This is the first integrative review of customers’ intentions to use Airbnb. We integrate what is currently known about customers’ intentions to use Airbnb and then provide a robust model for Airbnb use intentions that both researchers and practitioners can utilize.

This study aims to determine experimentally factors affecting the satisfaction of retail stock investors with various investor protection regulatory measures implemented by the Government of India and Securities and Exchange Board of India (SEBI). Also, an effort has been made to gauge the level of satisfaction of retail equities investors with the laws and guidelines developed by the Indian Government and SEBI for their invested funds.

To accomplish the study’s goals, a well-structured questionnaire was created with the help of a literature review, and copies of it were filled by Punjabi retail equities investors with the aid of stockbrokers, i.e. intermediaries. Amritsar, Jalandhar, Ludhiana and Mohali-area intermediaries were chosen using a random selection procedure. Xerox copies of the questionnaire were given to the intermediaries, who were then asked to collect responses from their clients. Some intermediaries requested the researcher to sit in their offices to collect responses from their clients. Only 373 questionnaires out of 1,000 questionnaires that were provided had been received back. Only 328 copies were correctly filled by the equity investors. To conduct the analysis, 328 copies, which were fully completed, were used as data. The appropriate approaches, such as descriptives, factor analysis and ordinal regression analysis, were used to study the data.

With the aid of factor analysis, four factors have been identified that influence investors’ satisfaction with various investor protection regulatory measures implemented by government and SEBI regulations, including regulations addressing primary and secondary market dealings, rules for investor awareness and protection, rules to prevent company malpractices and laws for corporate governance and investor protection. The impact of these four components on investor satisfaction has been investigated using ordinal regression analysis. The pseudo-R-square statistics for the ordinal regression model demonstrated the model’s capacity for the explanation. The findings suggested that a significant amount of the overall satisfaction score about the various investor protection measures implemented by the government/SEBI has been explained by the regression model.

A study could be conducted to analyse the perspective of various stakeholders towards the disclosures made and norms followed by corporate houses. The current study may be expanded to cover the entire nation because it is only at the state level currently. It might be conceivable to examine how investments made in the retail capital market affect investors in rural areas. The influence of reforms on the functioning of stock markets could potentially be examined through another study. It could be possible to undertake a study on female investors’ knowledge about retail investment trends. The effect of digital stock trading could be examined in India. The effect of technological innovations on capital markets can be studied.

This research would be extremely useful to regulators in developing policies to protect retail equities investors. Investors are required to be safeguarded and protected to deal freely in the securities market, so they should be given more freedom in terms of investor protection measures. Stock exchanges should have the potential to bring about technological advancements in trading to protect investors from any kind of financial loss. Since the government has the power to create rules and regulations to strengthen investor protection. So, this research will be extremely useful to the government.

This work has societal ramifications. Because when adequate rules and regulations are in place to safeguard investors, they will be able to invest freely. Companies will use capital wisely and profitably. Companies should undertake tasks towards corporate social responsibility out of profits because corporate houses are part and parcel of society only.

Many investors may lack the necessary expertise to make sound financial judgments. They might not be aware of the entire risk-reward profile of various investment options. However, they must know various investor protection measures taken by the Government of India & Securities and Exchange Board of India (SEBI) to safeguard their interests. Investors must be well-informed on the precautions to take while dealing with market intermediaries, as well as in the stock market.