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Amidst unpredictable and turbulent periods, such as the COVID-19 pandemic, service organization’s responses are required to be innovative, adaptable and resilient. The purpose of this study is to explore the utilization of both reconfiguration and transformational strategies as instruments for cultivating resilience and advancing sustainability in service organizations.

The study examines a proposed resilience model using fuzzy logic. The research also used a semantic differential scale to capture nuanced and intricate attitudes. Finally, to augment the validity of the resilience model, a measurement scale was formulated using business mathematics and expert opinions.

Although investing in resilience training can help organizations gain control and maintain their operations in times of crisis, it may not directly help service organizations understand the external turmoil, seek available resources or create adaptive remedies. Conversely, high levels of reconfiguration and transformation management vigour empower a service organization’s revolutionary, malleable vision, organizational structure and decision-making processes, welcoming talented and innovative employees to enhance capabilities during crises.

The resilience model bestows a comprehensive understanding of the pertinence of building resilience for service organizations identifying the antecedents that influence the adoption of these strategies and introduces a range of theoretical perspectives that empowers service organizations to conceptualize and plan for building resilience. The research guides service organizations to become more resilient to external shocks and adapt to changing circumstances by diversifying their offerings, optimizing their resources and adopting flexible work arrangements. The study elaborates on the enhancement of resilience, increasing innovation, improving efficiency and enhancing customer satisfaction for service organizations to remain competitive and contribute to positive social and economic outcomes through the adoption of both reconfiguration and transformational strategies.

The study also guides the service organizations to become more resilient to external shocks and adapt to changing circumstances by diversifying their offerings, optimizing their resources and adopting flexible work arrangements. Rapid innovation and business model innovation are essential components, enabling service organizations to foster a culture of innovation and remain competitive. In addition, the adoption can lead to improved financial performance, job creation and economic growth, contributing to positive social and economic impacts.

The resilience model bestows a comprehensive understanding of the pertinence of building resilience for service organizations. It identifies the antecedents that influence the adoption of these strategies and introduces a range of theoretical perspectives that empowers service organizations to conceptualize and plan for building resilience. The research also provides a foundation for further investigation into the effectiveness of these strategies and their impact on organizational performance and sustainability. By better preparing service organizations for disruptions and uncertainties, this research triggers ameliorated organizational performance and sustainability.

Within the realm of the service industry, the present investigation has undertaken the development, quantification and scrutiny of both resilience and tenacity. In addition, it has delved into the intricate dynamics surrounding the influencing factors and antecedents that bear upon resilience, elucidating their consequential impact on the operational performance and outlook of service-oriented organizations. The findings derived from this research furnish valuable insights germane to enhancing operational efficacy and surmounting impediments within the sector.

The purpose of this paper is to establish the link between three constructs, namely, service innovation, corporate reputation (CR), and word-of-mouth (hereinafter WOM). Primarily, the aim is to understand whether innovation in a service firm drives its reputation, thereby resulting in positive WOM where the direct effect of service innovation of a firm on WOM is mediated by reputation. Furthermore, the study also seeks to understand whether the type of service firm has an effect on determining the level of the mediation effect.

This study adopts an integrated approach where the measure for the construct service innovation is explored through a qualitative approach, and the conceptual model is estimated through path analysis. The service industry taken for this study is banking, and the through non-probability criterion sampling technique, 252 customers responded to their level of agreement. The PLS-SEM technique was used to estimate the path coefficient by following the two-stage approach. The multigroup moderation analysis is performed to determine whether the type of the bank plays a major role in determining the direct effects and the mediation effect of CR between service innovation and WOM.

The result of this study indicates that there is a strong positive association between the three constructs. Further, the direct relationship between service innovation and WOM is partially mediated by reputation. The result of the multigroup moderation indicates that the type of the bank plays a major role in determining the mediation effect of reputation.

The study helps the decision makers and the managers of the bank to understand that frequent innovation within the firm would help to gain reputation, and thereby customers would tend to give a positive WOM. Further, non-reputable firms can still gain a positive WOM if they continuously innovate new services. In the Indian context, it is noted that there is a difference between private and public banks in determining the mediation effect of reputation between service innovation and WOM.

The originality of the study is based on the following: development of a unique scale to measure service innovation in the banking industry overcoming the existing scales which are based on goods-dominant logic; estimating empirically the combined effect of service innovation and CR on WOM; the process of evaluating the moderated mediation effect; how the mediating effect of CR varies from private sector banks to public sector banks.

The study aims to emphasize the need for an exclusive theory, approach and measurement scale for service innovation. In the past three decades, the importance of services and service-related industry has grown tremendously. Well-established scales used for research in manufacturing cannot be directly adopted and measured in the service industry. This article follows the synthesis approach by including both technological and non-technological typologies for measuring service innovation. This is followed by reporting the effect of service innovation on outcome performances. The context of the study is the higher education sector.

An integrated research design was used to collect data from students in various parts of south India. In total, two focus group discussions and three in-depth interviews were conducted for item generation. Confirmatory factor analysis was performed for the reliability and validity of the scale. The study developed the HEd-INNOSERV scale consisting of seven dimensions comprising 34 items.

The study developed the HEd-INNOSERV scale consisting of seven dimensions comprising 34 items. The empirical results demonstrate that the scale is reliable, valid and generalizable across higher education institutions (HEIs). The scope for future research is to develop a generalized scale that can measure across the entire service sector.

The scale shall help researchers in testing the conceptual models earlier developed in the service innovation domain. Similarly, HEIs could measure their stakeholders' perceptions of their innovation activity. Further, the result indicates that innovation enhances the reputation of the institution, which ultimately results in positive word of mouth.

Commercialization of the scale by developing an appropriate algorithm would help institutions in measuring their innovation-led initiatives continually and establish quality and standards. The scale can be used complementarily with other measures adopted from regulatory and rating agencies.

The HEd-INNOSERV scale shall help in optimizing the existing business processes of HEIs by helping them consciously introduce appropriate technological and non-technological innovations.

Intervention strategies are designed by policymakers to impact people by effectively changing the environment in which people make decisions. Many government-led agencies and nongovernmental organizations promote behavioral change by adopting social marketing strategies. Social marketing uses the application of commercial ideas to influence the voluntary behavior of individuals. Under these circumstances, this study aims to examine the effect of these emerging brand-building techniques social marketing especially in public campaign.

This descriptive study collected opinions related to the constructs from 324 respondents across India. This study used statistical package for the social science and Smart partial leased square software to test the validity of the hypotheses.

The results of this study indicate that when the campaigns target the emotional state of the consumer, he or she crosses all boundaries like physical attributes, service parameter or even any form of assessment and provides incremental value to the campaign, thus forming a favorable behavior.

This study provides insights on how emotional branding can be used for better involvement and relationship building, which leads to long-term engagement with the customers. The marketers can also get facilitated through this study by developing a new perspective of creating their advertisements through emotional branding techniques, especially with a focus on corporate social responsibility in the global environment.

In recent times, marketers have adopted a new communication strategy to build their brand through promotions that might appeal directly to customer’s emotional state, popularly termed as “emotional branding.” This new communication strategy aims at creating and nurturing a relationship between the consumer and the brand by accumulating memories, emotions, personal narratives and expectations.

Candlestick charts are a key tool for the technical analysis of cryptocurrency price fluctuations. It is essential to examine trends in the time series of a financial asset when completing an analysis. To accurately examine its potential future performance, it must also consider how it has changed and been active during the period. The researchers created cryptocurrency trading algorithms in this study based on the traditional candlestick pattern.

The data includes information on Bitcoin prices from early 2012 until 2021. Only the engulfing Candlestick model was able to anticipate changes in the price movements of Bitcoin. The traditional Harami model does not work with Bitcoin trading platforms because it has yet to generate profitable business results. An inverted Harami is a successful cryptocurrency trading method.

The inverted Harami approach accounts for 6.98 profit factor (PrF) and 74–50% of profitable (Pr) transactions, which favors a particularly long position. Additionally, the study discovered that almost all analyzed candlestick patterns forecast longer trends greater than shorter trends.

To statistically study its future potential return, examining how it has changed and been active over the years is necessary. Such valuations are the basis for trading strategies that could help traders and investors in the cryptocurrency market. Without sacrificing clarity or ease of application, the proposed approach has increased performance by up to 32.5% of mean absolute error (MAE).

This study is novel in that it used multilayer autoregressive neural network (MARN) models with crypto-net (CNM) in machine learning to analyze a time series of financial cryptocurrencies. Here, the primary study deals with time trends extracted through a neural network model. Then, the developed model was tested using Bitcoin and Ethereum. Finally, CNM validity was tested through linear regression.

Usage of updated technology is continuously empowering customer relationship management (CRM) to be convenient and user friendly, where customers are kept engaged with knowledge and information. This enables them on decision-making and managing their portfolio, especially in mutual fund investments. To improve toward a positive decision, certain quality related variables needed to be considered. Thus, this study aims to estimate the mediation effect of relationship quality and outcome (RQO) between CRM and investment decision-making in mutual funds (MFD).

The descriptive study adopted the constructs from existing empirical literatures to conceptualize the model with three higher order constructs with 12 dimensions. Survey method is used, and with a structured questionnaire, a total of 323 mutual fund investors were approached using nonprobability criterion sampling technique, of which 262 relevant responses were considered for estimating the structural model. Smart PLS was used to establish the relationship of the constructs.

The result emphasizes a significant direct and indirect relationship indicating that investors are more inclined to MFD through technology-enabled CRM and RQO plays a vital role in explaining the direct relationship between CRM and MFD. The results of the study are in-line with the existing literature.

The study highlights that financial institutions must focus not only on technological diffusion but also needs to ensure quality service by providing knowledge and information during every access of transactions by customers, making them independent and confident during investments.

This study indicates how capacity efficiency, which is a part of service productivity, can be managed without affecting the outcome efficiency by incorporating technology in the place of human interaction during relationship acquiring and retaining process.

This paper aims to examine the moderated mediation effect of the lack of students’ socialization (as one of the COVID-19 consequences) and the university reputation on the relationship between the service innovation and students satisfaction. The relationship between students satisfaction and their loyalty is also examined.

This study adopts a quantitative research approach, whereas the study population consists of all universities’ students in Lebanon. Data were collected from 201 students, elected depending on snowballing sample technique. A questionnaire was used to gather data, whereby partial least squares structural equation modeling was used to check the proposed scales validity and the relationships between the study variables.

The findings reveal a significant direct effect for university’s service innovation on students satisfaction and an indirect effect through the mediation role for university reputation. Moreover, an evidence for weak negative significant effect for lack of socialization on students satisfaction exists. Whereby, lack of socialization does not moderate the relationship between university service innovation and students satisfaction. Finally, students satisfaction has a significant positive effect on their loyalty.

This paper advances the service innovation literature in the higher education sector. In addition, the paper might be the first paper to address the influence of lack of socialization as one of the COVID-19 consequences on students satisfaction. Furthermore, areas for future research are suggested.

This chapter examines the manner in which a disaster-affected population of artisanal fishers relocated inland to new sites following the Indian Ocean tsunami of 2004 experienced and adapted to problems of water quality, scarcity, sanitation, and drainage. While numerous studies of conflicts over water tend to focus on issues of equitable access (see Anand, 2011), this chapter seeks to link the problem to the contested priorities driving land and resource use and access. I show how inland relocation negatively impacted households, making it harder to sustain livelihoods due to distance from the coast, while imposing new costs including that of commodified and scarce water, locational deficiencies, and the structural weaknesses of new housing. Placed in a historical context, the problem of water can be seen as an aspect of the long-term problem of ecologically unequal exchange pitting local artisanal fisher communities against an aggressively state-supported commercial fishery sector. The continuity I seek to hone in on is the pattern of imposing costs on fishers while enabling the alienation and privatization of coastal resources. Taking water not only as a vital substance presenting questions of access and quality but also as a problem of drainage and effluence enables a fuller consideration of how the unequal distribution of costs on poorer populations became legitimized in the name of recovery. At the same time, the chapter also highlights the manner in which fishers refused to remain docile subjects of power and used their agency and autonomy in adapting to and sometimes refusing the terms of relocation.

The purpose of this paper is to describe an approach towards code validation of RISC microcontrollers, which helps to automate software debugging. A static machine code analysis which checks the appropriateness of instructions in a sequence to identify any logical mistakes and also to identify redundant codes appearing in a program for the target processor is presented.

Validation is done with the help of rules of inferences formulated for the target processor. The rules govern the occurrence of illegitimate/out of place instructions and code sequences for executing the computational and integrated peripheral functions. The stipulated rules are encoded in propositional logic formulae and their compliance is tested in all possible execution paths of the application programs. An incorrect sequence of machine code pattern is identified using slicing techniques on the control flow graph generated from machine code.

The results explain that the technique is independent of compiler/assembler and contributes to early detection of software bugs that are otherwise hard to detect. Program states are identified mainly with machine code pattern, which drastically reduces the state space creation contributing to an improved state‐of‐the‐art model checking.

Though the technique described is general, the implementation is highly architecture oriented, and hence the feasibility study is conducted only on PIC16F87X microcontrollers.

This validation tool can be integrated to the system development environment resulting in improved software quality and reduced debugging time.

It is a novel and original approach at machine code level applicable to a wide range of processors once appropriate rules are available.