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The purpose of this study is to identify the drivers and future scenarios of Iran’s Social Security Organization.

The research is applied in terms of orientation and mixed in terms of methodology. In this research, the methods of theme analysis, root definitions, fuzzy Delphi and Cocoso were used. The theoretical population is the managers and senior experts of the social security organization, and the sampling method was done in a judgmental way. The tools of data collection were interviews and questionnaires. The interview tool was used to extract the main and subdrivers of the research and develop the scenarios.

Through theme analysis, 35 subdrivers were extracted in the form of economic, sociocultural, financial and investment, policy, marketing, environmental and legal themes. Due to the large number of subdrivers, these factors were screened with fuzzy Delphi. Eleven drivers had defuzzied coefficient higher than 0.7 and were selected for final prioritization. The final drivers were prioritized with the CoCoSo technique, and the two drivers of social security holdings governance and state of government revenues had the highest priority. Based on these two drivers, four scenarios of prosperity, resilient social security, unstable development and collapse have been developed.

Some of the suggestions of the research are: using the capacity of FinTechs and financial startups to invest the government revenues of the organization, using digital technologies such as business intelligence for more efficient decisions and developing corporate governance in the organization.

The trend toward subscription economy accelerated the rise of access-based consumption models for durable consumer goods, replacing individual ownership with subscription contracts. At the same time, disruptive platform businesses have arisen in several consumer markets, bypassing traditional value chains while growing through network effects. In a conceptual approach, the authors address the future market for durable consumer goods in light of developments toward access-based consumption, subscription models and platform business models.

In a conceptual approach, the authors apply a scenario analysis following the Framework Foresight method and address trends, constants, plans and projections shaping the future market of subscriptions for durable goods. The authors create a baseline scenario and two alternative scenarios for the future of consumer durables and thereby discuss platform growth stages and implications for manufacturer brands.

The rising market power of platform companies leads to a baseline scenario where these platforms enter the market of subscriptions for durable goods. Alternative scenario 1 addresses the successful market entry of new platform businesses. In contrast, alternative scenario 2 describes the rise of manufacturer brand platforms.

This conceptual research enriches the discussion of access-based business models by creating scenarios depicting possible future developments. Moreover, it adds to the increasing focus on platform business models and thereby addresses the role of traditional manufacturer brands in markets for durable consumer goods subscriptions.

As a company’s corporate social responsibility (CSR) image can protect from the backlash of a service failure, it is important to remind customers of the company’s CSR commitment when a service failure occurs. One novel mechanism for doing so is through a prosocial service recovery. However, explorations of such service recovery strategies are relatively unknown. Thus, this paper aims to examine how recoveries including prosocial elements compare to those only utilizing monetary compensation strategies and to explore boundary conditions for such effects.

This research utilizes an experimental design approach across three studies. Participants were recruited from Amazon’s Mechanical Turk.

This research demonstrates that a recovery including prosocial (vs only monetary) elements can positively impact purchase intent through the firms’ CSR perceptions. The authors show that the benefits of prosocial compensation are contingent on the motivation for visiting a company (e.g. hedonic vs utilitarian) as well as the degree to which the company is perceived as luxurious.

The series of studies provides important theoretical contributions to services marketers by advancing the understanding of novel recovery strategies and demonstrating when companies should initiate such strategies. Implications of the findings and directions for future research are explored.

The Open API (application programming interface) architecture will play an important role in promoting future FinTech service applications; however, it involves user data, and the current specialization and progression are less visible. Therefore, an evaluation framework for Open API development in the FinTech service ecosystem is constructed in this study.

This study preliminarily selects the four most important key objects and factors of this ecosystem and conducts expert interviews to revise the evaluation framework. Then, this study uses the fuzzy analytic hierarchy process (FAHP) to evaluate the objects and their factor weights and finally uses the FAHP analysis results to further apply the evaluation based on distance from average solution (EDAS) approach to explore the strategy optimization scenarios.

According to the analysis results, the co-creation object and productivity object are the two most significant objects, with weights of 0.275 and 0.272, respectively. The analysis shows that FinTech-related companies expect to increase productivity through co-creation. Finally, the results also indicate that mobile payment is the best Open API application scenario in the FinTech service ecosystem, followed by online banking. These results illustrate strategic and management implications.

This study screens key evaluation criteria with a literature review and expert questionnaire interviews to process quantitative research. It can determine the weights of objectives and criteria to clarify the strength of influence between the objectives and criteria. Next, this study measures the probable performance of Open API applied in various FinTech service ecosystem scenarios.

Although trade volumes in e-retailing have increased significantly in recent years, logistics service failures are inevitable, especially at the delivery stage. Therefore, it is essential to provide customers with effective recovery strategies to increase their satisfaction and repurchase intentions. There is a lack of empirical evidence on whether the response time or the discount offered in compensation is more crucial for customers. Therefore, this study aims to determine whether the response time or the discount offered for high and low criticality failures has a greater impact on customer satisfaction levels and repurchase intentions for female and male customers.

A scenario-based experimental design method has been adopted to collect data, and 697 participants aged 18 and 58 years have been reached. The research utilized a between-subjects design, incorporating three factors: gender (female vs male), criticality (high vs low) and compensation (7 days: 10% discount, 10 days: 20% discount and 14 days: 30% discount). Six scenarios depicting the failure of an online retailer were created, and factorial univariate ANOVA was conducted to test the hypotheses.

The study's results show that in terms of customer satisfaction, female customers attach more importance to the response time in the case of high criticality and the amount of discount offered in the case of low criticality. On the other hand, male customers give more importance to the response time in terms of customer satisfaction when they experience a high or low criticality failure. In the case of low criticality, response time is more important for male customers to increase their repurchase intentions, while the amount of the discount is more important for female customers.

The study demonstrates the relative importance of the response time and discount amount according to the criticality level of failures and to guide business managers in terms of the recovery strategies they will implement. It focuses on gender differences and determine whether the response time or discount amount is more important for male and female customers in high or low-criticality situations.

Customer lifetime value (CLV) is one of the key indicators to measure the success or health of an organization. How can an organization assess the organization's customers' lifetime value (LTV) and offer relevant strategies to retain prospective and profitable customers? This study offers an integrated view of different methods for calculating CLVs for both loyalty members and non-membership customers.

This study outlines eleven methods for calculating CLV considering (1) the deterministic aspect of NPV (Net present value) models in both finite and infinite timespans, (2) the geometric pattern and (3) the probabilistic aspect of parameter estimates through simulation modeling along with (4) the migration models for including “the probability that customers will return in the future” as a key input for CLV calculation.

The CLV models are validated in the context of complementary and alternative medicine (CAM)in the healthcare industry. The results show that understanding CLV can help the organization develop strategies to retain valuable customers while maintaining profit margins.

The integrated CLV models provide an overview of the mathematical estimation of LTVs depending on the nature of the customers and the business circumstances and can be applied to other business settings.

The purpose of this study was to examine the mediating effect of three coping strategies (i.e. active, expressive, and denial coping) in the relationships between service failures (i.e. high- and low-contact service failures) and negative behavioral intentions (i.e. switching intention).

The critical incident technique (CIT) was used to identify the conceptually categorized service failure types in the fitness industry, and then confirmatory factor analysis (CFA) and structural equation modeling (SEM) were performed to examine the mediating effect of coping strategies among high-contact service failure and switching intention (study 1) and the mediating effect of coping strategies among low-contact service failure and switching intention (study 2).

While the mediating effect of coping strategies was significant in the relationship between high-contact service failures (study 1) and negative behaviors (i.e. switching intention and complaints), it was not significant in the relationship between low-contact service failures (study 2) and switching intention. Out of the three coping strategies, the impact of active coping was significant.

This study extends the understanding of the mediating effect of coping strategies in the relation between high- and low-contact service failures and switching intention.

This paper aims to explore the impacts of a blockchain network implementation to support purchasing processes of a Brazilian public organization.

The Grumbach method was used to build the scenarios. Five experts with knowledge in blockchain and experience in public procurement were consulted on 20 possible preliminary events, defining their probability of occurrence and relevance. The data obtained were processed in Puma software, which returned a selection of ten definitive events, based on probability, relevance and standard deviation indicators, generating a map of prospective scenarios.

Three following scenarios are shown, the ideal scenario, the one with greater implantation benefits and fewer complications; the trend scenario, more likely to occur under current conditions; and the most likely scenario of occurrence, according to experts. The results indicated which simulated events are drivers (motives), and which are influenced (dependent). They were categorized as opportunities or threats to the deployment of the technology.

Although public procurement processes are standardized by Brazilian legislation, new events may arise from the replication of the model in different organizations. The research revealed the need for practical testing in a simulated public procurement environment.

The article explores the interaction between disruptive network technology and processes linked to public sector efficiency. Studies on electronic government point to the future of public management.

Service failures usually occur in front of third-party customers. Third-party customers react emotionally and behaviorally to service failure and recovery efforts aimed at focal customers. However, there is a gap in the literature on how third-party customers react to a service failures incident and a recovery over another customer, depending on how socially close or distant they are from. This study investigates the effect of third-party customers' emotions on consumer forgiveness, negative word-of-mouth (WoM) and repatronage intentions in the service recovery process by comparing close and distant third-party customers.

This study utilizes a 2 (social distance to the focal customer: close, distant) × 2 (service recovery: yes, no) between-subjects design. The authors used a scenario-based experiment to test the proposed hypotheses. A total of 576 respondents were involved in the study.

The results from the authors' scenario-based experimental study show that positive and negative emotions felt by distant third-party customers are higher than those of close third-party customers. In addition, the effect of positive emotions on customer forgiveness is more substantial for distant third-party customers. Third, moderated-mediation analysis indicates that social distance has a moderator effect only on the relationship between positive emotions and customer forgiveness.

This study contributes to the service literature by comparing socially close and socially distant third-party customers' reactions to service failure and recovery attempts.

Early studies projected potential societal, economic and environmental benefits by the widespread deployment of Autonomous and Connected Transport (ACT) promising a significant reduction of transport costs and improvement in road safety. An effective way of assessing ACT impact is via simulations, where results are largely affected by the scenarios defining the ACT development. However, modelled scenarios are very diverse due to the huge uncertainty in ACT development and deployment. This chapter aims to shed light on the different ACT simulation scenarios and sustainability aspects that should be considered while developing or reporting the simulation results. To this end, this chapter discusses the various simulation approaches, what the required (or the typically utilised) pipelines are, and how some components are more important or less important than in ‘classic’ modelling and simulation approaches. Special focus is dedicated to the uncertainty related to ACT operational parameters and how these will impact transport modelling. To address said uncertainty, an analysis of current approaches to scenario building is provided, as the chapter guides the reader through different methodologies and clusters them in relation to the desired indicators. Finally, the chapter identifies and proposes Key Performance Indicators (KPIs) that are useful when applying simulation tools to assess ACT scenarios. These KPIs can be used for simulation scenario development to test particular sustainability aspects of ACT deployment and relevant policies.