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This study aims to examine the impact of consumer risk appetite, biases (specifically negative recency bias), and the importance of reviews in enhancing information quality. By analyzing these variables, the authors gain insights into their role in enriching the overall information spectrum available to consumers. The findings contribute to a better understanding of how risk appetite, biases and consumer reviews shape the quality of information.

The questionnaire assessed the relationship between dependent and independent variables by asking participants to rate their experiences in relevant scenarios. Variance-based structural equation modeling with the ADANCO program was used to examine the data. ADANCO software is used explicitly for variance-based structural equation modeling. To evaluate research models and test hypotheses, partial least square path modeling is used.

The efficiency of reviews and ratings is greatly influenced by consumer risk appetite. Businesses should focus on clients who are willing to take risks and balance positive and negative feedback. It is essential to comprehend how customers understand reviews. Credibility is increased by taking biases into account and encouraging unbiased criticism. Promoting thorough reviews strengthens influence. Monitoring and making use of these elements improve online reputation and commercial success.

The research has limitations due to the simplicity of the attributes taken into account and the requirement for a larger sample size. Overcoming barriers to promote consistent client feedback is essential, and tailored emails can help with assessment generation. Increased customer participation in writing evaluations can be achieved by removing obstacles and highlighting the advantages of participation.

Businesses and buyers rely on this “organically” generated content as the basis of their promotional strategy and buying decisions. Most of the research is related to consumer reviews, their behavior and the importance of social validation. However, some critical aspects related to this need further investigation.

The challenges facing 21st-century society are becoming increasingly complex, requiring the development of new citizen competencies. This study aims to validate an educational model focused on developing complex thinking in higher education students. Current educational models lack future-ready competencies, necessitating the emergence of new models to guide future generations toward the common good.

This was an adaptation of the causal-layered analysis (CLA) applied to 415 participants from higher education institutions in Mexico, Panama and Spain. Sessions were designed to present the proposed educational model and explore participants’ perceptions of its significance and contributions to future education.

Key findings include the following: participants perceived complexity as difficult and challenging; causes of problems were linked to outdated educational models requiring replacement by those that develop students’ competencies; participants envisioned changes that would develop individuals capable of understanding and transforming society; and participants recognized the model’s transformative potential, offering a novel proposal for 21st-century education.

This research sought to gather opinions from different stakeholders using the CLA methodology, providing a deep understanding of participants’ perspectives on the proposed solution.

This study aims to examine the enablers of productivity of enterprise-level Agile development process using modified total interpretative structural modeling (TISM). The two main objectives of the current study are to determine the variables influencing enterprise-level agile development productivity and to develop modified TISM for the corresponding components.

To identify enablers of the productivity of enterprise-level agile software development process a literature review and opinions of domain experts were collected. A hierarchical relationship among variables that show direct and indirect influence is created using the modified TISM (M-TISM) technique with Cross Impact Matrix-Multiplication Applied to Classification analysis. This study examined and analyzed the relationships between the determinants within the enterprise using a M-TISM technique.

With the literature review, the study could identify ten enabling factors of the productivity of Agile development process at the enterprise level. Results depict that program increment (PI) planning and scalable backlog management, continuous integration and continuous delivery (CI/CD), agile release trains (ART), agile work culture, delivery excellence, lean and DevOps practices, value stream mapping (VMS), team skills and expertise, collaborative culture, agile coaching, customer engagement have an impact on the productivity of enterprise-level Agile development process. The results show that team collaboration, agile ways of working and customer engagement have a greater impact on productivity improvement for enterprise-level Agile development process.

The developed model is useful for organizations employing scaled Agile development processes in software development. This study provides a recommended listing of key enablers, that may enable productivity improvements in the Agile development process at the enterprise level. Strategists should focus on team collaboration and Agile project management. This study offers a modified TISM model to academicians to help them understand the effects of numerous variables on maintaining the productivity of an enterprise-level Agile. The identified characteristics and their hierarchical structure can help project managers during the execution of Agile projects at the enterprise level, more effectively, increasing their success and productivity.

The study addresses the gap in the literature by interpretative relationships between the identified enabling factors. The model validation is carried out by a panel of nine experts from several information technology organizations deploying Agile software development at the enterprise level. This unique method broadens the knowledge base in Agile software development at scale and provides project managers and practitioners with a practical foundation.

This study aims to develop a modular and prescriptive digital transformation maturity model whose constituent elements have conceptual integrity as well as reveal the priority weights of maturity model components.

A literature review with a concept-centric analysis enlightens the characteristics of constituent parts and reveals the gaps for each component. Therefore, the interdependency network among model dimensions and priority weights are identified using decision-making trial and evaluation laboratory (DEMATEL)-based analytic network process (ANP) method, including 19 industrial experts, and the results are robustly validated with three different analyses. Finally, the applicability of the developed maturity model and the constituent elements are validated in the context of the manufacturing industry with two case applications through a strict protocol.

Results obtained from DEMATEL-based ANP suggest that smart processes with a priority weight of 17.91% are the most important subdimension for reaching higher digital maturity. Customer integration and value, with a priority weight of 17.30%, is the second most important subdimension and talented employee, with 16.24%, is the third most important subdimension.

The developed maturity model enables companies to make factual assessments with specially designed measurement instrument including incrementally evolved questions, prioritize action fields and investment strategies according to maturity index calculations and adapt to the dynamic change in the environment with spiral maturity level identification.

A novel spiral maturity level identification is proposed with conceptual consistency for evolutionary progress to adapt to dynamic change. A measurement instrument that is incrementally structured with 234 statements and a measurement method that is based on the priority weights and leads to calculating the maturity index are designed to assess digital maturity, create an improvement roadmap to reach higher maturity levels and prioritize actions and investments without any external support and assistance.

Financing remains a serious concern for firms and is considered the main hurdle in the growth and development of small and medium enterprises (SMEs). Recently, a new stream of financing (SCF; supply chain finance) has emerged to meet the financing issues of SMEs. Therefore, measuring SCF is essential to support SMEs’ operations. This study aims to develop and validate the SCF scale based on extant literature.

Using a mixed-method approach, this study recruited different samples of SME entrepreneurs to confirm the internal consistency, assess construct validity and check the item structure of the SCF scale in AMOS.

The outcomes of confirmatory factor analysis demonstrated the six factors of SCF (inventory financing, working capital optimization, reverse financing, fixed assets financing, logistics financing and order cycle financing) spread over 21 items. An interitem solid structure of the SCF scale offers invaluable contributions to the supply chain management literature.

This research supports SME entrepreneurs to obtain secure financing at the best cost, mitigating the risk of default, supporting the buyers’ payment terms, providing early payment to suppliers and strengthening the firm’s value chains. SMEs can obtain financing per their requirements to support their operational business processes. Moreover, SMEs can plan, manage and control finance-related transactional activities by correctly identifying financing solutions.

The present study contributes to SCM literature by developing and validating the SCF scale. To the best of the author’s knowledge, this is the first study that redefined SCF and identified its six dimensions.

The global market for cloud gaming is growing rapidly. How gamers evaluate the service quality of this emerging form of cloud service has become a critical issue for both researchers and practitioners. Building on the literature on service quality and software as a service, this study develops and validates a gamer-centric measurement instrument for cloud gaming service quality.

A three-step measurement instrument development process, including item generation, scale development and instrument testing, was adopted to conceptualize and operationalize cloud gaming service quality.

Cloud gaming service quality consists of two second-order constructs of support service quality and technical service quality with seven first-order dimensions, namely rapport, responsiveness, reliability, compatibility, ubiquity, smoothness and comprehensiveness. The instrument exhibits desirable psychometric properties.

Practitioners can use this new measurement instrument to evaluate gamers' perceptions toward their service and to identify areas for improvement.

This study contributes to the service quality literature by utilizing qualitative and quantitative approaches to develop and validate a new measurement instrument of service quality in the context of cloud gaming and by identifying new dimensions (compatibility, ubiquity, smoothness and comprehensiveness) specific to it.

Clean and sustainable energy becomes an alternative to differentiate electricity suppliers, but it is necessary to have a better understanding of their behaviour to achieve green customer loyalty. This paper aims to deploy a behavioural model that helps explain loyalty of customers towards green electricity providers by including a series of antecedents such as trust, satisfaction, perceived environmental impact, propensity to trust and perceived risk.

The paper deploys a behavioural model that it is tested through structural equation modelling to a sample of 231 German electricity consumers with green contracts. The data analysis included two steps: first, the development and validation of the scales used to measure the constructs proposed in the model, and second, the model test.

Results demonstrate that trust and satisfaction directly influence loyalty, while satisfaction and the other variables included in the model have an indirect relationship with loyalty mediated by trust and satisfaction. As green characteristics of electricity are difficult to evaluate, managers should demonstrate in their communication the environmental effects of their activities while emphasising their capacity to attend to supply requirements for building long-term customer relationships.

The paper is focused on the understanding of those consumers who have signed a green electricity contract and the antecedents associated to their loyalty. The behavioural model helps identify how managers should apply marketing strategies to foster green consumers loyalty.

Nowadays, in many organizations, products are not delivered instantly. So, the customers should wait to receive their needed products, which will form a queueing-inventory model. Waiting a long time in the queue to receive products may cause dissatisfaction and churn of loyal customers, which can be a significant loss for organizations. Although many studies have been done on queueing-inventory models, more practical models in this area are needed, such as considering customer prioritization. Moreover, in many models, minimizing the total cost for the organization has been overlooked.

This paper will compare several machine learning (ML) algorithms to prioritize customers. Moreover, benefiting from the best ML algorithm, customers will be categorized into different classes based on their value and importance. Finally, a mathematical model will be developed to determine the allocation policy of on-hand products to each group of customers through multi-channel service retailing to minimize the organization’s total costs and increase the loyal customers' satisfaction level.

To investigate the application of the proposed method, a real-life case study on vaccine distribution at Imam Khomeini Hospital in Tehran has been addressed to ensure model validation. The proposed model’s accuracy was assessed as excellent based on the results generated by the ML algorithms, problem modeling and case study.

Prioritizing customers based on their value with the help of ML algorithms and optimizing the waiting queues to reduce customers' waiting time based on a mathematical model could lead to an increase in satisfaction levels among loyal customers and prevent their churn. This study’s uniqueness lies in its focus on determining the policy in which customers receive products based on their value in the queue, which is a relatively rare topic of research in queueing management systems. Additionally, the results obtained from the study provide strong validation for the model’s functionality.

The purpose of this study is to identify the business strategies that entrepreneurs have formulated to establish the business with the intention of scaling up in the information technology (IT) sector in Chile, given that they have managed to scale up sustainably at an average annual rate of 73.3% and an average annual employee growth rate of 37% for four consecutive years after an establishment period of 25 months.

Three methodological steps were used to identify which strategic initiatives are relevant to the establishment of small- and medium-sized enterprises (SMEs) on the path to scaling up. The first part consisted of identifying the literature and defining the research propositions and research questions. The second part was to prepare, collect and analyse the data to conduct the research by applying, transcribing, reviewing and coding the sources of evidence to explore how SMEs are able to develop strategic initiatives for the start-up process. The final stage was to validate the research proposal to identify potential strategic initiatives identified during the multi-case study.

As a result of the data analysis and empirical findings, three deliberate strategic initiatives were identified: staying engaged with customers, delivering successful business solutions and articulating social capital. However, in crisis situations, entrepreneurs readjust their strategies based on their management skills and an emergent strategic initiative was identified as securing the financial structure and revolutionising change. While this research was not designed to identify personal attributes, it did highlight the importance of adaptation and learning as a skill to drive the business model for scaling up during the establishment of their business.

It is clear that the study focused on Chile and cannot be replicated in other regions or sectors due to the characteristics of the sample itself, but it provides empirical evidence that there are cycles prior to scale up that need to be understood. The findings were empirically validated during the establishment phase, but the deliberate and emergent strategic initiatives that consolidated the SME to prepare for its scale-up process are not evident in the theory.

The IT sector will continue to grow and change after the pandemic, and the global economy will use more digital systems, creating new ways of working with the use of IT. This context will impact on SMEs where strategies, whether deliberate or emergent, will need to be part of the new business models, and therefore, caution should be exercised when using the results of this study. Public and private institutions should educate and guide entrepreneurs for the potential scaling up of their SMEs without having to wait 42 months, according to Global Entrepreneurship Monitor 2021-2022 (Hill et al., 2022). Scaling up can begin as early as 25 months after establishment, breaking the paradigm of the theory that the SME must be established in a period of 3.5 years. This period cannot be generalised as business opportunities in the IT sector are faster. The research also contributes by reporting that contingency planning is relevant during the establishment phase.

Educational institutions and the public sector have made efforts to change business cultures regarding the importance of strengthening entrepreneurship, but teaching the emergent strategies that often challenge SME creation is not yet widespread in educational formats. This is a challenge not only for institutions but also for entrepreneurs trying to anticipate the constant changes in the global economy. This research provides an opportunity to create more dynamic business models with more conscious risk planning.

Although the literature has confirmed the findings, this research has provided a pre-scaling picture that links these two important stages on the axis of deliberate and emergent strategies. The findings confirm the importance of correctly embedding five strategic initiatives for the establishment of the SME if it is to continue on its journey towards business scale-up. However, there is a lack of empirical evidence in emerging economies on how entrepreneurs have found the right path to scale-up.

This study aims to explore the effects of remote work on employee productivity and innovation and how these effects are moderated by knowledge sharing and digital business intensity.

The study draws on survey data from a random sample of 231 remote workers across the USA. The analysis and empirical validation of the research model used partial least square.

The results demonstrate a positive association between remote work and employee productivity. In addition, the findings present empirical support for hitherto anecdotal evidence regarding the impact of remote work on innovation. In particular, the study notes that knowledge sharing and digital business intensity amplified the positive relationship between remote work and employee productivity. The results further revealed that the positive link between remote work and innovation was stronger in the presence of knowledge sharing.

The study contributes to the ongoing inquiry into remote work by drawing on the knowledge-based view as an underlying lens to understand the consequence of remote work. Identifying knowledge sharing and digital business intensity as moderators of the linkage between remote work and employee productivity is an important contribution, especially when researchers and practitioners are trying to understand the business value of working remotely. Furthermore, to the best of the authors’ knowledge, this study is the first to identify knowledge sharing as a key mechanism that strengthens innovation outcomes in a remote work environment.