Usable Responses Research Articles

Understanding Customer Readiness for Digital Gamification

ABSTRACT Digital gamification has been studied extensively in different contexts across information systems and digital marketing. Interestingly, scholarly studies in information systems/marketing regarding the benefits of digital gamification are mixed, with several research works reporting negative outcomes. Our study attempts to resolve these contradictions and explain why digital gamification failed in certain instances—the target customers were not ready. The present study, done in the USA covering 446 usable responses, adds to the extant literature in many ways. First, we throw light on gamified engagement programs and the mediating role of customer readiness and consequent outcomes. Our results reveal that simplicity and information quality are other important dimensions of gamified engagement programs, in addition to intrinsic and extrinsic game dynamics, for achieving adequate customer readiness. Additionally, customer participation makes the greatest contribution to company engagement, followed by program loyalty and program satisfaction. We conclude with the study’s implications on different fronts.

What motivates U.S. restaurant customers to choose plant-based meat alternative dishes?

ABSTRACT The purpose of this study is to examine how different consumption values influence consumer intentions to choose a dish featuring plant-based meat alternatives at a restaurant by applying the theory of consumption values. The present study also investigates the mediating role of attitude in the relationships between values and consumer intentions. Responses were collected through the Qualtrics panel service and structural equation modeling was employed to analyze the data. The results, based on a total of 682 usable panel responses, indicate that emotional and epistemic values acted as significant driving forces, directly promoting consumers’ intention. Attitude was aroused by distinctive, functional, emotional, and conditional values and in turn, significantly impacted intention. Furthermore, it was found that attitude fully mediated the relationship between conditional value and intention. The results offer useful implications for restaurants that offer menus with plant-based meat alternatives.

Discursive Practices during an Electoral Cycle: Public Opinion and Political Disillusionment on Twitter

Electoral cycles are highly charged, politically intense moments that influence public discourse. Political elites, citizens, and the traditional news media seek to generate opinions and interactions on social networks. This research is motivated by the following questions: What are the communicative and deliberative practices used in these spaces? Is it possible to identify the characteristics that –through deliberative conversations– potentially foster or undermine democratic debate, particularly when using populist and polarizing discourse? Using a mixed methods approach, we apply a social network analysis tool to track conversations and identify the volume of political discourse (N=346,000). Using selective and staged filtering, we identified posts from nine Peruvian Twitter accounts during the September 2022 electoral campaign in Lima: three candidates, three media outlets, and three accounts with high levels of engagement. Our data comprised the comments from these nine accounts and was extracted using an Application Programming Interface (API). Subsequently, we carried out ethnographic content analysis on publications with more than 30 comments. In this phase, we analyzed Twitter comments using a codebook to identify deliberative practices and user responses. Our findings underscore the significant role of principal media outlets in shaping political conversation on Twitter. We also discovered that attempts to interact and deliberate were often overshadowed by heated comments attempting to impose opinions on others. Most importantly, our research reveals a widespread disillusionment with politics, political institutions, and even the political preferences of fellow citizens in Peru, highlighting a key challenge for democratic discourse on social media.

The design of listening tests for impact noise annoyance ratings

Noise annoyance is characterized by irritation, discomfort, disturbance or distraction. The evaluation of impact noise based on user response provides useful information about subjective auditory perception. These assessments are carried out by participants in listening tests under laboratory conditions, where participants usually rate the annoyance caused by different samples of impact noise. The question arises as to whether it is possible to gain a meaningful insight into the human inner life by evaluating only a single quality such as annoyance. Therefore, other qualities such as loudness, allowance limit or naturalness are also included in the rating procedure. In this paper we present the design of the listening test for impact noise annoyance and the corresponding selection of investigated qualities. It describes why they were selected and how the evaluation was carried out. It also describes how descriptive qualities have been used in other studies. The technical implementation of the listening procedure is presented and correlations between the ratings of the different qualities are discussed.

The Role of Digital Transformation in Enhancing Business Performance and Smart Economy Integration: A Case Study of Thailand’s Retail Industry

This research examines the relationship between digital transformation, business performance, and the smart economy. The study uses a purposive sampling method with a quota approach, targeting business owners or managers from traditional retail businesses in smart cities across Thailand. 389 usable responses were collected and analyzed in Structural Equation Modeling (SEM). Digital transformation positively correlates with business performance. Moreover, both digital transformation and business performance positively impact the smart economy. The findings support that digital transformation enhances business performance and contributes to the smart economy in retail operations, improving customer experiences and fostering smart economies. This study advances the academic understanding of digital transformation in Thailand’s retail sector, confirming the relevance of the TOE framework. The findings provide practical insights for retail businesses seeking to enhance performance and integrate with the smart economy through digital transformation.

Investigating the Dynamics of Workforce Stability: The Influence of Perceived Employability on Career Resilience, Task Performance, Learning Agility and Employee Retention

The main purpose of this study is to analyze the complex interrelationships among perceived employability, employee task performance, employee retention, career resilience, and learning agility to cover this knowledge gap and provide HR practices and policies supported by evidence that can increase service sector development and contribute to Saudi Arabia's economic goals. The study used a cross-sectional quantitative design and conducted an online survey of employees in the service sector of Saudi Arabia. Snowball sampling was used during the data collection, and 403 usable responses were collected and utilized for data analysis. Data analysis techniques included descriptive statistics, Pearson correlation, and composite assessment analyses were conducted through SPSS 28. For hypothesis testing, the PLS-SEM model was used through SmartPLS4. R2adj, standardized root means square residual, Normed fit index, and Q2predict were used for model evaluation. The research findings highlighted the importance of perceived employability which is positively related to task performance and retention and show the need for organizations to train their employees so that they are characterized by career resilience and learning agility, which relate positively on their task performance and their retention within the Saudi service industry. Acquiring knowledge and understanding regarding these relationships is essential to develop targeted practices and policies to improve employee outcomes and elevate the organization's competitiveness in an economy undergoing rapid transformations. This study's findings provide practical implications regarding human resource management and organizational development strategies in Saudi Arabia that will support future research by enhancing perceived employability, building career resilience, developing employee task performance, improving learning agility, and ensuring a higher rate of employee retention, realizing the significance of each element in developing organizational goals and success. Keywords: perceived employability, employee task performance, employee retention, career resilience, learning agility.

Development of the accounting practicum e-book and analysis of student responses to its use

This study aims to develop an E-Book for accounting practicum and evaluate user responses to its implementation. A needs analysis revealed that 48 out of 51 students lacked access to learning resources and required instructional media, correlating with their suboptimal learning outcomes. The research utilizes a Research and Development (R&D) approach, specifically employing the 4D model. The Technology Acceptance Model (TAM) Questionnaire was administered to gauge user feedback. The participants included 51 eleventh-grade students from SMKS Filadelfia Pemangkat. Data analysis involved both qualitative and quantitative descriptive methods to address the research questions regarding the E-Book's design, user feedback, and any significant disparities in responses based on socio-economic status. The E-Book, developed using Canva and edited with Heyzine, comprises 2 chapters, 4 videos, 2 Excel files, and 2 online quizzes. User responses from small and large group trials were overwhelmingly positive, categorized as "Strongly Agree." Further analysis indicated that students from higher socio-economic backgrounds had a higher median score (3.95) compared to those from moderate (3.50) and underprivileged backgrounds (3.00). These findings suggest significant differences in user responses based on socio-economic status.

The Mediating Role of Brand Love between Brand Personality and Brand Loyalty: A Study on SMEs Traditional Woven Fabric in Indonesia

This paper aimed to examine the impact of brand personality dimensions (sincerity, excitement, and competence) on brand loyalty. In addition, the role of brand love is explored through mediation models. A total of 384 valid and usable responses collected from a consumer of Traditional SME Traditional Woven fabric in Indonesia were analyzed through the structural equation model (SEM). A research model examined several hypotheses underpinned by multidimensional brand loyalty and interpersonal love. The findings showed that sincerity and competence had a significant impact on brand loyalty and brand love, but excitement had no significant impact on brand loyalty and brand love. Moreover, brand love mediated the relationship between sincerity and competence, but excitement had an insignificant impact. The results of this study indicate that small and medium-sized enterprises (SMEs) in the traditional woven fabric industry should foster emotions to establish a robust consumer-brand connection. Furthermore, it is critical to prioritize the development of robust attributes, as traditional woven textiles possess deeply ingrained cultural significance. This study contributes to the current knowledge of brand loyalty literature by exploring the characteristics of brand personality and brand love. The findings imply that when consumers' brand personality is mixed with brand love, it will result in increased loyalty towards the brand.

Personal Characteristics of Youths and Their Influences on Sexual Health Information Seeking

The primary aim of this research is to examine how youths in the Klang Valley utilize social media to seek information about sexual health issues, particularly premarital heterosexuality. By investigating this relatively unexplored area, the study aims to address a gap in the existing literature concerning the use of social media as a technology to seek sexual health information among youths in the Klang Valley. A survey technique was employed to collect data from youths aged between 18 and 24 years old who knew about sexual health issues caused by premarital heterosexuality. Three hundred eighty-four usable responses were received and analyzed using appropriate statistical procedures. The Partial Least Squares Structural Equation Modeling (SmartPLS 4.0) technique was used to test the research model. The study confirmed that user personal characteristics, which were problem recognition and involvement, enabled youths in the Klang Valley to seek sexual health information through social media. The empirical results of this study also led to several significant findings. The findings indicated that user personal characteristics directly influenced the use of social media for sexual health information. The platform's usefulness and abundance of sexual health information aided youths in the management of sexual health issues. Overall, social media plays an essential role as a platform for youths to seek sexual health information in Malaysia. Keywords: Premarital heterosexuality, youth, social media, Technology Acceptance Model, information-seeking.

Impact of External Auditors’ Ethical Behavior on Audit Quality: A Client Perspective

Purpose: This study explores the impact of external auditors' ethical behavior on audit quality, with a particular focus on the perspectives of internal auditors in publicly listed Pakistani companies. It aims to address the gap in literature concerning the interplay between ethical behavior, corporate ethical values, and perceived audit quality. Design/Methodology/Approach: Using Structural Equation Modeling (SEM), the study examines the direct and indirect effects of external auditors' ethics on audit quality, with corporate ethical values as a moderating factor. Data were collected via a mail survey and Google Forms from auditors in listed Pakistani firms, yielding 232 usable responses (61% response rate). The analysis utilized SPSS and AMOS for reliability, validity, factor analysis, regression, and correlation. Findings: Results reveal a positive relationship between ethical behavior and perceived audit quality, amplified by strong corporate ethical values. Companies prioritizing ethics reported enhanced audit quality, providing valuable insights for regulators and auditors. Implications/Originality/Value: This research contributes to the understanding of ethical behavior in audit quality, offering actionable insights for improving ethical standards in audit practices. The findings are pertinent for regulatory bodies, auditors, and policymakers aiming to strengthen financial disclosure integrity in Pakistan

How generative artificial intelligence portrays science: Interviewing ChatGPT from the perspective of different audience segments.

Generative artificial intelligence in general and ChatGPT in particular have risen in importance. ChatGPT is widely known and used increasingly as an information source for different topics, including science. It is therefore relevant to examine how ChatGPT portrays science and science-related issues. Research on this question is lacking, however. Hence, we simulate "interviews" with ChatGPT and reconstruct how it presents science, science communication, scientific misbehavior, and controversial scientific issues. Combining qualitative and quantitative content analysis, we find that, generally, ChatGPT portrays science largely as the STEM disciplines, in a positivist-empiricist way and a positive light. When comparing ChatGPT's responses to different simulated user profiles and responses from the GPT-3.5 and GPT-4 versions, we find similarities in that the scientific consensus on questions such as climate change, COVID-19 vaccinations, or astrology is consistently conveyed across them. Beyond these similarities in substance, however, pronounced differences are found in the personalization of responses to different user profiles and between GPT-3.5 and GPT-4.

Intention to Use FinTech Payments: The Perspectives of Benefits, Risks, and Openness to Change

Objective - The COVID-19 pandemic has significantly transformed many aspects of daily life, including the way payments are made. While the usage of cashless payments has increased, cash remains the main mode of payment in Malaysia. Therefore, this study aims to explore the factors driving the intention to use FinTech payments based on the Unified Theory of Acceptance and Use of Technology (UTAUT) with the Value-based Adoption Model (VAM). Methodology/Technique – 546 usable responses were collected using a stratified sampling technique across 13 states in Malaysia. Then, structural equation modeling using the partial least squares approach was applied to test the hypotheses. Finding – The findings show that performance expectancy, effort expectancy, social benefit, privacy risk, and openness to change are the significant determinants of intention to use FinTech payments. Openness to change was found to be the most significant predictor of intention to use FinTech payments. However, the study failed to confirm the impact of social influence, economic benefit, security risk, and regulatory support on the intention to use FinTech payments. This study does not fully validate the significance of UTAUT and VAM constructs. Novelty – To the best of our knowledge, this is the first study that uses the UTAUT and VAM on intention to use FinTech payments together with openness to change and regulatory support. This is a framework that covers the decision-making determinants from the perspectives of benefits, risks, individual characteristics, and the external environment. Type of Paper: Empirical JEL Classification: G23, G28, G29 Keywords: FinTech Payment, Intention to Use, UTAUT, VAM, Benefits, Risks Reference to this paper should be referred to as follows: Chen, N.H; Habibullah, M.S; Sapar, R. (2024). Intention to Use FinTech Payments: The Perspectives of Benefits, Risks, and Openness to Change, GATR-Global J. Bus. Soc. Sci. Review, 12(3), 91–113. https://doi.org/10.35609/gjbssr.2024.12.3(1)

Is a web-based Thai version of the work-related quality of work-life scale-2 a reasonable alternative to the paper-based version?

ABSTRACT This study investigates the suitability of a Thai web-based assessment tool for comprehensively evaluating the Work-Related Quality of Life (WRQoL). A descriptive study was conducted. The web-based questionnaire was distributed to health workers at the University Hospital of the Faculty of Medicine at Khon Kaen University, Khon Kaen, Thailand, via convenience sampling, yielding 290 usable responses after data cleaning. IBM SPSS and AMOS performed Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA). The results revealed enhanced internal consistency upon excluding 1 item (Q24) and delineated dimensions into 5 categories: homework interface and working conditions web-based (HWCW), web-based job and career satisfaction (JCSW), web-based general well-being (GWBW), web-based control at work (CAWW), and web-based stress at work (SAWW). This web-based assessment tool has potential advantages in technological convenience and interpretation accuracy. It offers a robust framework for assessing WRQoL dimensions and advancing workplace well-being assessment methodologies.

PENGEMBANGAN BUKU CERITA BERGAMBAR DIGITAL SEBAGAI MEDIA PEMBELAJARAN MEMBACA PEMAHAMAN SISWA SEKOLAH DASAR

The lack of reading comprehension skills in grade II elementary school students is the impetus for this research because reading media has the potential to improve reading comprehension skills. Researchers developed digital picture storybooks as a tool to help students gain reading comprehension to overcome this problem. The purpose of this study is to provide details about the development of picture storybooks that researchers will make, including development design, validation results, and user responses. Design and Development (D&D) using the Analysis, Design, Development, Implementation and Evaluation (ADDIE). The resulting product was assessed by 2 material experts, 2 media experts, and 22 student users. The material expert feasibility test received an overall average score of 86.5% with the criteria “very feasible”. Then the final results of the media expert feasibility test get an overall average score of 92.5% with the criteria “very feasible”. Based on the media trial, user responses were obtained which showed an overall average score of 94.75% with “very good” criteria for picture storybooks as a learning media for reading comprehension that had been developed. This research corroborates the finding that students tend to like digital media (electronic), gadgets, and connected to the internet.

An automated social media manager based on artificial intelligence

In today's world of social media, where brands and companies constantly interact with their audiences, the automation of content management processes is becoming increasingly important. Manual content creation, publication, and analysis on social networks require significant resources and time. Automated social media management systems based on artificial intelligence help simplify these processes, enhancing efficiency and optimizing audience engagement strategies. Artificial intelligence in social media marketing systems allows for the automation of tasks such as creating text posts, scheduling publications across different platforms, and analyzing user interactions. Artificial intelligence can analyze audience behavior, predict the optimal time for posts, and recommend changes to content strategies for maximum reach. This not only saves time but also improves the effectiveness of marketing campaigns through more accurate analytical data. However, the automation of social media marketing also faces challenges. The primary issues include the complexity of integrating different social networks into a single management system and the limitations in generating high-quality content that meets the emotional and stylistic requirements of the brand. Additionally, a major challenge is content personalization based on data analysis, which must account for each audience segment's unique needs and behavioral characteristics. Despite these challenges, the prospects for developing automated social media marketing managers are promising due to ongoing innovations in artificial intelligence and machine learning. Future research and development will focus on improving the quality of automated content generation, enhancing user interfaces, and integrating new social platforms to expand multi-channel marketing campaign management capabilities. Thus, the automation of social media marketing is a promising field that will enable brands and companies to optimize their audience engagement strategies while significantly reducing the time and resources required for content creation, publication, and analysis. This work presents the structure of the main entities of an automated social media management system based on artificial intelligence, including users, professions, questions, answers, settings, and integration with Telegram. The developed system enables efficient content management, automates publications, and personalizes audience interaction based on user responses. The system's described key components, attributes, and relationships provide scalability and flexibility, allowing brands and companies to optimize their marketing strategies and client interactions.

Development of Data-Driven Educational Decision Implementation Guidelines Assisted by Formative Tests in Science Learning

Data-Based Educational Decisions (DDED) is an important part of the learning process where DDED is used to improve the quality of learning. This research purpose to develop Data Driven Educational Decision Implementation Guidelines (DDED) supporting formative tests in IPA learning. DDED is an adaptation of Data Drive Decision Making (DDDM) in learning. DDED is based on Data Drive Decision Making (DDDM), which is a decision-making process that has been widely applied in the world of management. The DDED directs teachers to be adaptive and flexible in implementing various methods, models, teaching materials and learning media based on student access. The development design used is 4D which consists of defining, designing, developing and deploying. The content of the guidelines has been agreed through expert consensus through the fuzzy delphi technique. Fuzzy Delphi Method to create a broad and detailed understanding, especially in education. The consensus indicated that formative tests should include relevant questions and quizzes, comprising both multiple-choice and essay formats, aligning with the principles of DDED. The resulting guideline tests the level of validity and user response. Users respond well to the guidelines developed.

COMPARISON OF MACHINE LEARNING ALGORITHMS FOR SENTIMENT ANALYSIS OF DIGITAL IDENTITY APPLICATION USERS

In the rapidly evolving digital era, the Population Identity Application (IKD) plays a crucial role in streamlining civil administration processes in Indonesia, allowing easier and faster access to population services. This study aims to explore the application of machine learning algorithms in analyzing user responses to the IKD application. Three popular algorithms: Support Vector Machine (SVM), K-Nearest Neighbors (K-NN), and Naïve Bayes were chosen to classify sentiment from 1301 user reviews on the Google Play Store into positive and negative categories. After performing data preprocessing such as tokenization and stemming, hyperparameter optimization was conducted using GridSearchCV to enhance classification accuracy. The research results indicate that the SVM algorithm, optimized with hyperparameters, including the use of the rbf kernel and a parameter value of C = 1, achieved the highest accuracy of 85.60%, making it the most effective method for sentiment classification of the IKD application. These findings provide valuable insights for the government and developers in refining the features and performance of IKD, contributing to the efficiency and security of digital administration in Indonesia. Furthermore, this study opens opportunities for further development that is more responsive to user needs and expectations in the future.

A Comparison of Brand-Related Outcomes Between Naming Rights and Jersey Sponsorships in Professional Sport

Naming rights and jersey sponsorship are highly visible, offering numerous benefits to both brands and properties but at a particularly high cost. The purpose of this study was to examine individuals’ attitudes and behaviors toward naming rights and jersey sponsors. The study drew on the Persuasion Knowledge (PK) Model as a lens for differentiating between consumers’ responses to each sponsor. A between-group design was employed; two versions of a questionnaire (one for each sponsorship condition) were distributed to a nationwide sample of Canadians, yielding 331 usable responses. Findings suggested participants had better awareness of the naming rights sponsor than the jersey sponsor, but no attitudinal differences were observed. However, attitudinal differences were observed on team identification. Furthermore, it appears that the triggering process for PK may differ in the sport sponsorship setting than what is observed with traditional advertising, likely due to a moderating effect of team identification.

Drivers of Intrapreneurial Innovation: A Study of Individual Innovative Behaviour in Organisations

Organisations can gain a competitive edge through Intrapreneurial Behaviour (IB) by swiftly innovating and adapting to market changes. Research indicates that intrapreneurship plays a crucial role in the banking sector in achieving a competitive advantage. Organisations can enhance their intrapreneurial capability by leveraging Individual Innovative Behaviour (IIB). However, innovation in the banking sector is often constrained by strict regulations, high safety requirements, and a fundamental need for trust and stability. Therefore, it is important to embrace and stimulate factors that encourage and enable innovation. To our knowledge, research on how intrapreneurship can be stimulated and measured in the Dutch banking sector is currently lacking. Thus, developing indicators and metrics for measuring intrapreneurship in Dutch banks is essential. This study investigates the factors affecting IIB using a quantitative survey. Building on the connection between IB and IIB, IIB is treated as a dimension of IB. The perceived work context, comprising an organisation's entrepreneurial orientation and innovative climate, can empower employees' IIB in the digital era. This context encourages them to generate new ideas and engage in collaborative innovation without fear of failure, thus fostering IIB. Our study explores factors driving IIB, empowering employees to act as intrapreneurs through organisations perceived Entrepreneurial Orientation (EO) and Innovative Climate (IC), with Digital Maturity (DM) as a moderating variable. Data were collected in 2021 from the three largest Dutch banks, which hold over 43% of the market share. A snowball sampling method was used to reach Dutch bank managers knowledgeable about the study's key constructs. This method involved initial contact with human resources departments and managers within these banks. The survey was administered to 167 managers, yielding 125 usable responses (75% response rate). Results indicate that employees in the banking industry with high DM are more likely to engage in IIB when firms support EO strategies and IC, and when employees adopt self-leadership skills.

Analisis Sentimen pada Ekspedisi Kurir Online di Indonesia Menggunakan Algoritma Naive Bayes

This journal focuses on sentiment analysis of four popular online courier expeditions in Indonesia, namely JNT, JNE, Shoope Express, and Anteraja. The purpose of this research is to understand the opinions and responses of users towards the online courier expedition service. The research was conducted using the sentiment analysis method, which utilizes data from user reviews contained in each online courier application on the Playstore platform. In this study, the Naive Bayes algorithm is used to perform sentiment analysis. This algorithm was chosen with the aim of producing higher accuracy results in determining positive and negative sentiments from user reviews. By using this method, this research hopes to provide a deeper understanding of the perceptions and experiences of users of the online courier service under study. The results of the study show that there are variations in user sentiment for each online courier expedition. User reviews include aspects of satisfaction with service, desired complaints, and problems that often arise when using the online courier application. These findings provide valuable insights for online courier service providers, as it can help them improve service quality and customer satisfaction. By understanding user opinions and feedback, online courier service providers can identify deficiencies in their services and make necessary improvements.