Abstract

Customer lifetime value is one of the most important tasks for enterprises to maintain customer relationships. However, due to the limitations of using a single data mining method, the measurement of customer lifetime value under the condition of noncontractual relationship has always been a research difficulty. This paper focuses on customer value measurement and customer segmentation based on customer lifecycle value theory, and carries out customer value measurement and customer segmentation research from the perspective of customer value, and constructs customer segmentation model. This paper first conducts feature engineering, such as data selection, data preprocessing, data transformation, and knowledge discovery, and then conducts customer value segmentation based on machine learning algorithms and customer relationship management analysis models and builds a customer value segmentation identification model under the condition of noncontractual relationship. Finally, empirical analysis is carried out with the real customer transaction data of the actual online shopping platform, which verifies the validity and applicability of the customer segmentation method and value calculation method proposed in this paper.

Introduction

Since the 1980s, customer relationship management (CRM) has increasingly become the focus of academia and industry. Facts have proven that maintaining good relationships with specific customers can increase corporate profits and increase the significant advantages of enterprises in market competition [1]. Enterprises can classify customer categories based on customer consumption behavior, customer lifetime value and other information, identify customer value, and apply it to CRM [2]. Scientific and effective research on customer lifetime value is the primary task of customer relationship management, which is of great significance to enterprise marketing plans and strategies. Scholars have confirmed that effective customer lifetime value segmentation research can bring more profits to enterprises [3]. However, due to the inadequacy of previous research on customer data processing and the limitation of single data mining methods, it is difficult to fully mine customer behavior information. The accurate measurement of customer life cycle value under non contractual relationships has always been a research difficulty. Through a literature review, the current calculation of customer lifetime value under noncontractual relationships mainly includes Pareto/NBD and other probability models [4,5], VAR, and other time series models, as well as machine learning algorithms [6]. Especially in recent years, with the wide application of Big Data in business intelligence and analytics, companies can collect a large amount of personal transaction data from customers at low cost. These can be analyzed using an array of methods including: neural network models, decision tree models, random forests, generalized additive models (GAMs), multiple adaptive regression splines (MARS), classification and regression trees (CART), support vector machines (SVM) and other machine learning algorithms. These methods are useful for the application of customer lifetime value calculation.

Conclusion and outlook

This paper studies the connotation of customer lifetime value under the noncontractual relationship from two aspects of customer segmentation and calculation methods, and constructs the customer segmentation mode under the noncontractual relationship and the customer value segmentation recognition model based on machine learning algorithm. This paper uses feature engineering to process the data, and comprehensively applies RFM model, machine learning algorithm and other methods to ensure the rationality and feasibility of the research results. The main innovation points of this paper are as follows: (1) Define the measurement method of customer value, build a customer segmentation model based on customer value under the noncontractual relationship, mine the characteristics of segmented customer groups, and enrich the existing research on customer value segmentation; (2) In the preprocessing stage of customer consumption behavior information, feature engineering is used to map the original data space to the new feature vector space through the data preprocessing and transformation process, so that in the new feature space, the machine learning model can better mine the feature vector information and improve the classification results of the model; (3) The traditional RFM model and machine learning algorithms are combined to expand the research on customer segmentation and customer lifetime value under the condition of noncontractual relationship.

Abstract

Despite the growth in CRM installations, e-CRM projects still have a significant failure rate, even after substantial investments in CRM technology. High rates of failure mean that the current requirements for developing and designing CRM need to be analysed. It’s not enough to just look at data related to a service’s efficiency; it’s also crucial to consider the impact on the user experience and their overall level of satisfaction. Given that CRM is a people-centric business strategy, it’s pertinent to wonder how much progress may be made in a similarly people-centric field like Real Estate through the development and use of a user-centred design approach. This study aims to seamlessly integrate a mobile customer relationship management (m-CRM) system with an electronic customer relationship management (e-CRM) system to increase customer loyalty, satisfaction, and performance through a user-friendly interface. User research, preliminary interviews, five usability interviews, and satisfaction surveys confirmed the functionality implemented and for each iteration, an expert was used to evaluate it. For this artifact’s creation and assessment, the DSR technique was used, with each interview serving as a data point for the model. It was determined that the Desktop interface solution may improve this CRM’s ease of use and user satisfaction, thereby benefiting the real estate industry through strengthened connections and more straightforward oversight of professionals’ performances.

Introduction

In the 21st century, the ability to interchange and transfer data through the internet and online services has had a noticeable impact on our culture (Purbowo et al., 2017).

Acquisition costs are five to ten times higher than retention costs (Alotaibi and Rigas, 2012), therefore contemporary firms are constantly on the lookout for strategic advantages. There is an ongoing requirement to build client-focused activities to strengthen long-term customer relationships (Jelonek, 2015, Kimiloǧlu and Zarali, 2009). However, this objective is becoming increasingly difficult due to rapid technical advancements (Alotaibi and Rigas, 2012, Kimiloǧlu and Zarali, 2009).

Thus, each company must invest in a customized business strategy and information system (IS) to comprehend its customers’ needs and desires (Jelonek, 2015). These include identifying the most profitable clients, lowering costs connected with online customer administration, developing a targeted and individualized marketing campaign, and generating in revenue (Goy and Magro, 2012, Jelonek, 2015).

Conclusions

This project aimed to adapt a mobile app for real estate that uses CRM into an online interface, with a focus on enhancing client satisfaction, loyalty, and productivity – more detail about the end artefact can be seen here and also the investigation of it can be seen here. All features implemented in this artefact were the ones described in Table 1. The use of Design Thinking principles, including strict monitoring of usability interviews, led to the development of a desktop application with a solid scientific base and assessment of its needs. The resulting interface features filterable calendars and contact lists, real-time agent performance tracking via dashboards and analytics, client qualification tools, and business funnels.

Usability concepts defined during exploratory research helped build an agent-friendly desktop interface. The interface’s simplicity and pleasant colour palette were praised for their utility, as the Aesthetic-Usability Effect states. The task’s use of colour was complimented for its ability to provide quick, clear visual clues. The app’s great level of customization may improve its user base since almost every function can be customized. Its flexible interface demonstrates the tool’s efficiency.

Abstract

     While the strategic use of social media (SM) for enhancing firm performance has attracted much attention, little is known about it through the lens of business-to-business (B2B) small and medium-sized enterprises (SMEs). Building on the market-driven view and the dynamic capabilities view of competitive strategy, we examine SM use in a framework of market-sensing and customer-linking capabilities that influence firm performance. Our research model posits that market orientation stimulates SM use to enhance market-sensing capability thereby facilitating two customer-linking capabilities, namely customer relationship management and brand management, which collectively contribute to greater marketing performance and financial performance. Our research model is empirically tested using a survey of 143 UK B2B SMEs. The findings broadly support our theorization in which the strategic use of SM, an essential part of market-sensing capability, enhances customer-linking capabilities. Interestingly, although SM use influences brand management capability, its suggested influences on both customer relationship management capability and marketing performance occur only through the mediation of brand management capability. Both customer-linking capabilities positively influence marketing performance and in turn financial performance. Our findings provide novel conceptual and empirical advancement of how market-centric B2B SMEs strategically use SM to enhance their market-sensing and in turn customer-linking capabilities, and hence firm performance.

Introduction

     With the increased digitalization of marketing activities, marketing professionals are increasingly adopting social media (SM) as a strategic tool to effectively engage with customers and broader stakeholders (e.g. Chaker, Nowlin, Pivonka, Itani, and Agnihotri, 2022; Pardo, Pagani, and Savinien, 2022); develop new products (Du, Yalcinkaya, and Bstieler, 2016); increase brand awareness (Deng, Wang, Rod, and Ji, 2021); co-create value (Itani, Krush, Agnihotri, and Trainor, 2020); and improve firm performance (Cheng, Liu, Qi, and Wan, 2021). More and more researchers suggest that firms must have an SM presence since the strategic use of SM is increasingly seen to enhance firm competitiveness (e.g. Cartwright, Liu, and Raddats, 2021; Tiwary, Kumar, Sarraf, Kumar, and Rana, 2021).

     The likely gains from SM technologies are particularly evident in business markets where customers are more informed and less dependent on interactions with salespeople (Ancillai, Terho, Cardinali, and Pascucci, 2019). For example, leading large firms such as Adobe, IBM, and Maersk Line are increasingly using digital channels and SM to facilitate effective dialogue with customers (Ancillai et al., 2019). The growing evidence suggests that SM can be strategically used to facilitate an effective dialogue with customers (Kovac, 2016), create brand awareness, or differentiate the focal brand from the competition (e.g. Deng et al., 2021; Swani, Brown, and Mudambi, 2020), provide customer care, and/or improve firm performance, among others (e.g. Salo, 2017; Tiwary et al., 2021).

Conclusion

     Overall, our study examined the much-advocated and under-investigated strategic use of SM for enhanced B2B marketing strategy. We opted to focus on the B2B SME context where it argued that due to the resource-constrained operating environment experienced by SMEs, the use of SM platforms will be particularly beneficial due to easiness of implementation, low-cost accessibility, and cost-efficiency. We promised our inquiry on the dynamic capabilities view and Day’s (1994) seminal framework of capabilities in market-driven firms and theorized that the strategic use of SM provides a meaningful link between market orientation and CLC. Overall, our research model captures how the strategic use of SM strengthens MSC to effectively seize market opportunities through (re)developing two key CLC that drive enhanced marketing performance and in turn financial performance. Overall, the strategic use of SM remains a fertile ground for further inquiry in B2B marketing strategy context.

Abstract

This study contributes to the extant literature by empirically investigating the influence of Business-to-Business (B2B) firms’ technology readiness on information technology capability and artificial intelligence-based customer relationship management (AI-CRM) and finally, on relationship performance and social sustainability performance. We leverage primary data from 217 samples and examine the firm’s social sustainability performance. Drawing on the paradigm of dynamic capability view, we found that a B2B firm’s technology readiness has a positive relationship with information and communication technology and AI-CRM capability. Information and communication technology capability also has a positive and significant relationship with AI-CRM capability. B2B firms’ relationship performance has a significant and positive relationship with social sustainability performance. A key finding of this study is that a B2B firm’s information and communication technology capability mediates between technology readiness and AI-CRM capability. Additionally, industry dynamism also moderates the link between information and communication technology capability and AI-CRM capability.

Introduction

In this fourth industrial revolution era, data is the key to achieving success, and these data are generally large data sets mostly gathered in unstructured form (Dubey et al., 2020). Businesses have made significant progress in the last decade with the introduction of the fourth industrial revolution (I4.0) (Telukdarie et al., 2018). I4.0 technologies improve information sharing and supply chain visibility (Gunasekaran et al., 2017). Advanced information and communication technologies have taken business-to-business (B2B) firms to the next level with embedded big data analytics and artificial intelligence (AI) capability (Bag et al., 2021, Bag et al., 2021, Bag and Rahman, 2021, Chung et al., 2021). The exploration of Chatterjee et al. (2021d) demonstrates that artificial intelligence-supported customer relationship management (AI-CRM) systems can be of paramount significance for B2B firms in this fourth industrial revolution era to remain sustainable in their respective industry. Implementation of AI-CRM also requires a combination of various resources and firm capabilities, and this can be achieved through collaboration and cooperation (Teece et al., 1997). According to Lee (2004), firms must adapt to technological changes or they will not survive in long run. Therefore, industrial firms must check their technological readiness for fourth industrial revolution technologies (Samaranayake et al., 2017). Technology readiness requires the input of several key resources to further develop information and communication technology capability (ICT) (Gupta & George, 2016).

Conclusion

Every firm considers its marketing and sales department and its customers and business partners to be of central importance because they are the lifeline of any firm. The findings of this research indicate that customer relationship management is an important activity involved in the downstream part of the supply chain where the focal firm develops relationships with industrial dealers and wholesalers and industrial customers in the supply chain network. In this fourth industrial revolution, firms are benefitting from data-driven decision-making and AI-CRM has shown huge potential in improving customer management. The literature reveals that AI-CRM can improve a firm’s performance, but the literature on developing lower-order capabilities that can be helpful in building AI-CRM capability in B2B firms lacks investigation. In addition, its connection with social sustainability has been under-researched, if researched at all. The current study provides interesting insights based on an analysis of data collected from B2B firms. The findings reveal that the technology readiness of B2B firms in this fourth industrial revolution era is positively related to AI-CRM capability while ICT capability demonstrates a partial mediating role. Industry dynamism is found to act as a contextual variable under the association of information and communication technology capability and AI-CRM capability. In addition, it was found that AI-CRM capability improves relationship performance among B2B firms, which ultimately improves social sustainability performance. In other words, firms willing to improve social sustainability performance must aim to build AI-CRM capability.

Abstract

     Artificial intelligence integrated with customer relationship management (CRM) systems has revolutionized organizations’ means of analyzing their huge volumes of customer data. To effectively respond to and manage the opportunities and challenges that arise from this, organizations are developing competencies and processes that evolve their agility, fine-tuning them to the artificial intelligence customer service system (AICS) and wider digitalization setting. In this context, this study identifies the factors impacting the adoption of an AI-integrated CRM system (AICS) in agile organizations as a part of their digitalization strategy. Methodologically, the research builds its theoretical foundation on extant works to develop hypotheses and a corresponding conceptual model. The model is quantitatively validated through a survey across the spectrum of Indian companies, following expert-based pretesting and pilot testing, and subsequently it is statistically tested using the partial least squares structural equation modeling (PLS-SEM) technique. The results, contextualized against the backdrop of organizational agility, identify and elucidate the relationship between stakeholders and perceived value and easiness of AICS, between employee trust and attitude, and the influence of attitude and behavioral intention as key mediators towards AICS adoption. The findings are conclusively transcribed into tangible implications for practice and explicit avenues for future research.

Introduction

     This research is grounded in three unequivocal premises stemming from contemporary organizational realities and inescapable contextual business precincts. These are the customer-centric nature of business (focus), the increasing dependence of organizational operations on technology (means), and the ever-changing and unpredictable nature of the business environment that demands attitudinal and procedural agility to adapt swiftly and effectively to the changes for competitive advantage (aim). For the purposes of this research, these are practicably and generally transcribed into customer relationship management (CRM), digitalization and artificial intelligence (AI) systems, and applied agility. Thus, this paper studies artificial intelligence-integrated customer relationship management systems, in the context of organizational agility, as the intersection of the three most prominent notions – CRM, digitalization, and AI – of present business theory and practice, and with corresponding value and contribution to knowledge. Accurate analysis of customer data is an important CRM activity. Organizations perform such activities to extract the best information. But since the volume of customer data can be huge, we need to investigate how AI technology could manage and analyze so much data in an accurate and cost-effective way to achieve business success (Gnizy, 2019). Only using AI in a CRM system might suffice in a static business environment. However, since the business environment is ever-changing and unpredictable in nature, organizations should have apt procedural and attitudinal agility to quickly adapt to the changes to gain competitive advantage. Hence, we need to know how the intersection of agility and AICS could fetch competitive advantage for the organizations.

Findings and implications

The agility contextualization

     As already highlighted, extracting the full potential of AICS in organizations is also linked to the organization’s agile competencies. However, the true question arising from this is how should the organization be agile; in other words, what is the nature of this relationship and how can it be optimized? Agility, in this context, should not be considered a stand-alone capability but rather viewed as a collection of different specific competencies. These include adaptability, innovation, resilience, and sustainability (Holbeche, 2018). The study highlights that if the stakeholders of the organizations could understand the usefulness of AICS and feel that AICS is not that complex to use, they would be inclined to use it. For this to happen, the organization must be agile in extracting the potential of AICS by addressing the threats and challenges and by utilizing its capabilities in the best possible way (Overby, 2006). The organizations should be agile to structure their IT competencies to sense and respond to threats and uncertainty, which would develop stakeholders’ trust. The validated results show that PU impacts BI (β = 0.81, p < 0.01), whereas PEU impacts PU (β = 0.80, p < 0.01), and earlier studies (Venkatesh and Davis, 2000) have also supported these linkages. Validation shows that trust impacts attitude, and intention impacts adoption, which earlier studies (DeConick, 2010) also supported. It appears that the impacts of PU on ATT and TR on AICS are insignificant, contradicting some earlier studies. The possible reasons for such deviation and contradiction have been explained earlier in detail. This study identified the antecedents that predict attitude, intention, and adoption after studying different models and by subsequently conducting statistical validation of the conceptual model. Fig. 3 helps us to provide the relevant regression equations, which are shown below.

Abstract

     This study examines the effects of salespeople’s social media and customer relationship management (CRM) technology use on value co-creation through knowledge and the downstream impact on sales performance. Based on task-technology fit and self-determination theories, the findings reveal that social media, CRM technology, and their interaction support salespeople in their value co-creation efforts through the mediating role of knowledge enriched by these tools. The results indicate a significant moderating effect of salesperson job autonomy and sales quota ease in enhancing the relationship between knowledge and value co-creation. The study concludes by discussing important implications that stem from our analyses.

Introduction

     In recent years, the sales profession has embraced knowledge generation and sharing as well as value co-creation functions as crucial elements of organizational effectiveness [1–4]. This shift has encouraged salespeople to function as knowledge brokers and to co-create value by sharing information with their customers to achieve sales performance outcomes [5,6]. To co-create value, salespeople must display a mastery-level understanding of the product, service, or idea they sell and of the market, competitors, and customers. Analogously, the business-to-business (B2B) market has experienced disruption with new tools that dramatically alter the sales profession. For example, social media tools (e.g., LinkedIn) have forced salespeople to focus on new methods (e.g., social selling) to gain customer information and understand customer needs. Social media is defined as “the technological component of the communication, transaction and relationship building functions of a business which leverages the network of customers and prospects to promote value co-creation” (p. 308) [7], and it is critical for an organization’s value co-creation functions. In accord, recent research has explored the role of social media in driving employees’ work behaviors. For instance, a recent article shows that social media use is related to employee stress appraisals [8]. Similarly, other studies have shown that social media use in the workplace is related to employee satisfaction, turnover intention, and performance [9,10]. These studies have focused on the role of social media in aiding salespeople to co-create value with the customers [10–12]. This line of research also parallels research that focuses on assessing the role of information technology systems in enhancing organizational performance [12–17].

Discussion, implications, and directions for future research

Discussion

      The market’s progression toward knowledge-based sales exchanges [6] has resulted in a knowledge-centric sales approach, but it has also created a need for efficient ways for salespeople to collect information and practice their knowledge with their customers. Simultaneously, the advancement in social media and CRM technologies supports the need to integrate both systems to provide additional sources for salespeople to enhance their knowledge about products and customers’ needs and to increase sales performance. An exploration of the role of knowledge in the framework is important in the sales context because, as argued before, salespeople are expected to work as knowledge brokers [6] and hence are required to display their knowledge when interacting with the customers. Past research has also highlighted the importance of salesperson’s technical know-how of not only the products they sell but also the competitors [55,148]. Moreover, scholars have also posited that knowledgeable salespeople have strong customer-serving abilities [71] that have direct implications for the firm’s financial performance. Because of the importance of salesperson’s knowledge, we extend the notion that social media can lead to knowledge generation and dissemination [33] by applying the framework at the individual salesperson level. While knowledge can be gained with prior experience, it is also essential to underscore that the salesperson’s knowledge can also be enriched most by a high use of CRM and social media. In other words, sales knowledge also depends on using different information and communication systems available for salespeople, including social media and CRM technology. It is also vital to highlight the importance of using social media as an add-on with CRM technology. The two channels can complement each other to provide the salesperson with better opportunities to learn more about customers’ needs and market conditions, leading them to co-create value with customers and increase their own sales performance. Recent scholars have analyzed the importance of social media in driving work outcomes [12,15].

Abstract

     In the emerging retail market, e-tailers operating in developing economies have to cope with the rapid use of the Internet, new electronic purchasing methods and online selling platforms. However, e-tailers do not understand the effect patterns in which customer engagement on purchase intention and customer acquisition. From e-tailers’ perspective, this study explores how customer engagement behaviors are related to both purchase intention and customer acquisition. We obtained live streaming data in the mature e-tail live streaming market environment and found empirical evidence supporting the conceptual framework through regression model analysis. The analysis results show that the specific indicators of the customer engagement are not all positively related to customer purchase intention and customer acquisition, and it is worth noting that the influence of “like” behavior on customer acquisition is no statistical significance. This is expected to encourage e-tailers to rethink their focus on customer acquisition and sales enhancement digital strategies as they operate in emerging markets.

Introduction

     Live streaming e-commerce has become the fastest growing new form of e-commerce in the world in the last three years. According to data from T-mall in China, within 48h of the 618 shopping festival in 2021, the live streaming e-commerce transaction volume of brand stores increased by more than 100% compared to the same period last year, and the number of live broadcast rooms of stores with a transaction of more than 10 million yuan was more than twice that of the same period last year. “Improve business efficiency through Taobao Live” has been recognized by many brands. And many international brands have used Taobao Live to reach Chinese consumers. Live streaming e-commerce has also been widely concerned with consumers in its novel form of commodity display, affordable and convenient. According to the 47th Statistical Report on Internet Development in China (CINIC, 2021), as of December 2020, the scale of online streaming users in China has reached 388 million, and 66.2% of online consumers have bought live streaming merchandise. Live streaming provides customers with added value and additional channels for customer engagement, making it a popular shopping method among consumers. Whether from the perspective of consumers or e-tailers, live streaming will become the mainstream e-commerce mode, as consumers will not change once their shopping patterns are formed.

Conclusion

     At a broader level, this paper was motivated by the observation that e-tailers do not understand the effect patterns in which live streaming service on their benefit, i.e., purchase intention and customer acquisition. The notion of engaging is reflected by customer co-creative and interactive experiences (Vargo and Lusch, 2008), so we focus on the customer engagement in the context of live streaming.

     Based on the prior research and data availability, we firstly determined the customer engagement behavior indicators (customer visits, likes and comments) in the context of live streaming. Then, we revealed the relationship between these engagement behavior indicators and purchase intention and customer acquisition, respectively, through empirical analysis. Consistent with most studies, customer engagement has a positive effect on purchase intentions, but the degree of impact varies across engagement behaviors, and, for customer acquisition, some engagement behaviors even have a negative impact. Overall, the finding of this paper highlights the important point that different engagement behaviors may have different effects. The retail business may benefit more from studies segmenting these engagement behaviors. Of course, the lack of access to specific data measuring increased sales and increased customers is a major limitation of our study, and in the future, we hope to work with brands to obtain specific data to further validate the findings of this study. While the limitations of our study go beyond this, our findings provide some inspiration for future researchers in the areas of live streaming e-commerce, customer engagement, and relationship marketing.

Abstract

Keywords

1. Introduction

2. Literature review

2.1. Employee-based brand equity

2.2. Customer relationship management dimensions

2.2.1. Customer orientation

2.2.2. Knowledge management

2.2.3. CRM organization

2.2.4. Technology based CRM

3. Methodology

4. Analysis of results

4.1. Common method Bias

4.2. Descriptive statistics

4.3. Measurement model

4.4. Structural model

5. Discussion and conclusion

6. Limitations and future research

Appendix A. Factor loadings of remaining items based on CFA results

References

Abstract

     The purpose of this study was to explore the effect of customer relationship management (CRM) dimensions on employee-based brand equity. By looking at the past literature, it can be noticed that the majority of earlier studies on brand equity examined it from customers’ perspective, while the employees’ perspective received less emphasis. Thus, the required data was obtained using a survey tool from 164 employees in the ride-hailing industry in Saudi Arabia. The obtained data was analyzed by the Covariance-Based Structural Equation Modeling (CB-SEM) method to test the hypothesis and reach at conclusions. The findings showed that CRM in general has a positive effect on employee-based brand equity. Specifically, it was found that CRM organization has a significant positive impact on employee-based brand equity. It was also verified that knowledge management and customer orientation have positive effects on overall employee-based brand equity. Finally, the results confirmed that technology-based CRM has a significant positive impact on employee-based brand equity. These results add to the body of literature on this topic and verify the significance of customer relationship management dimensions in affecting employee-based brand equity.

Introduction

     The topic of brand equity has received a noteworthy attention from several scholars since the last decades. The examination of brand equity has mainly been centered towards determining the factors that could improve brand value (Dinçer, Bozaykut-Buk, Emir, Yuksel, & Ashill, 2019). Although the concept has many definitions in the previous literature, there is a universal agreement that brand equity symbolizes the tangible and intangible value of a firm’s products or services that are devised from the unique name of the brand (Srivastava & Shocker, 1991). A strong brand equity provides noteworthy implications to firms, their clients, and to the investors as well. It enables the service providers to generates several benefits, such as: charging higher prices than the rivals for similar products, maintaining business customers on the long term even though competitors peruse price cutting strategies, and withstanding negative information about the failure of a certain product or service (Gelb & Rangarajan, 2014). High brand equity also permits firms to use the same brand name when they successfully introduce a new product. As the competition has increased recently among businesses and due to the imitation of a brand’s offerings, the acquisition of a reliable and trustworthy brand name has been regarded as the key distinguishing element. According to Augusto and Torres (2018); and Phung, Ly, and Nguyen (2019), a firm that acquires high brand equity tends to have greater trust from its consumers. Moreover, Poulis and Wisker (2016) tested the effect of employee-based brand equity on organizational performance and found that the attachment of employees to a brand represents the main factor that contributes to better financial outcomes.

Results and analyses

     As stated above, the collected data were analyzed using the CB-SEM approach. In order to check the likely existence of common-method variance bias among constructs, this paper relied on the CFA and single factor test of Harman (1960), and full collinearity test of Kock and Lynn’s (2012). When all of the measurement items of the constructs were constrained to be loaded on one single common factor, the overall variance explained by a general latent variable was lower than the Harmin’s threshold value of 50%, indicating that the final model is considered free from common method bias. Additionally, all of the Variance Inflation Factors (VIFs) in a full collinearity test were less than 5, suggesting that there is no indication of existing pathological collinearity (Podsakoff, MacKenzie, Lee, & Podsakoff, 2003).

Introduction

Literature review

Research methodology

Classification and analysis

CRM in hospitality and related themes

Discussion and future research

Limitations

References

ABSTRACT

This study reviews research articles published in the area of Customer Relationship Management (CRM) in the hospitality industry. The aim of this article is to systematically review the entire hospitality CRM literature to identify topical themes and trends. For this systematic literature review, four databases, namely, Elsevier, Emerald Insight, Sage, and Taylor and Francis were chosen to identify the research work published in the said arena. A total of 136 articles with 9900 citations in 46 journals were chosen from the four databases as they contained the relevant articles. These research papers were reviewed and classified based on their year of publication, journal of publication, databases, topics and key themes that emerged over the years. The gaps and trends were also identified to suggest further scope of research.

Introduction

The global hospitality industry is on the upward trajectory, with numbers of consumers increasing every year. The flourishing travel and tourism industry is one of the reasons for growth in the hospitality sector. The hospitality industry which is a customer-centric industry relies heavily on customers’ information and therefore Customer Relationship Management (CRM) is implemented worldwide in this sector (Sigala, 2005). A research was carried out by Yoo, Lee, and Bai (2011) on significant trends in the hospitality industry, which states that CRM is one of the most popular research topics for hospitality industry academicians. The research and consultancy organization Gartner (2018) states that $39.5 billion US dollars were spent on CRM software in the year 2017 and the market will grow at 16%. CRM has also been cited among the top five significant technologies in the world (Luftman et al., 2012).

Customer relationship management (CRM) is always considered as an essential task for increasing customer satisfaction for mobile banking (m-banking), and it is, like other areas of marketing, constantly evolving and updating. Also the vast use of the mobile banking by internet users, persuades electronic banking to use customer relationship management system in adoption mbanking. In this paper, the effects of using CRM system in the adoption m-banking on customer satisfaction and interaction, which is considered as the most important factor in the success of banking industry, is analyzed. The case studies of this paper are Iran top e-banks and the sample population chosen, are the customers of these banks, and a conceptual model is suggested to analyze the use of adoption of mobile banking on customer interaction and satisfaction. Factors that are introduced as influencing variables in this model on the customer satisfaction and interaction are: affective commitment, trust, loyalty, willingness to re-visit, number of visits, profitability, and Involvement. Collecting information in this article is performed by completing 243 questionnaires by staff of the communication with customers sector of these banks and their customers. The results of the statistical analyses conducted on these data indicate that all the variables addressed in the model, have a positive impact on the customer relationship and satisfaction except the trust.

Introduction

The bank’s ability to create and maintain customer satisfaction, is a key index which may strongly determine the success of the business. In order to create and keep up the competition with other competitors, it is necessary that banks try to provide superior service to customers so as to increase customer satisfaction. To achieve this, it is very important that banks carefully understand customer needs and discover their desires, and be able to provide products or services to customers that meet their demand or exceed their expectations. In these particular cases, the customer relationship management (CRM) can help the bank reach this important task. while the traditional CRM is executed through software systems and data bases, and is usually used by large banks, there is evidence that mobile banking, as an emerging phenomenon, are utilized to facilitate the implementation of the CRM by small banks (Trainer et al., 2014; Wu et al., 2005; Zhao, 2015). The emergence of the mobile banking, changed the way people communicate with each other and made organizations and banks to run their own websites on mobile banking so that they can communicate and interact directly with their customers (Martinez et al. 2013; Hajli et al., 2014; Malthouse et al., 2013;). On the one hand, the mobile banking has the power turn offline customers who are not a member of electronic banking, into online customer; and on the other hand it is highly permeable and timely because of the viral information spread (Kaplan et al. 2010).

Despite the importance of institutional factors in adopting new technologies, the role of these drivers in the use of social media technology (SMT) to strengthen customer relationship management (CRM) capabilities and improve company performance has not yet been investigated. First, drawing from institutional theory and capabilities theory, we analyze the influence of customer coercive pressure and competitor mimetic pressure on SMT use. Second, we investigate the mediator role of CRM capabilities in the relationship between SMT use and firm performance. The study’s results reveal that both institutional factors drive SMT use, their effects varying according to the size of the firm, its innovativeness, the sector and the market in which it operates. CRM capabilities were found to only indirectly mediate the relationship between SMT use and firm performance. From the study results, we derive managerial recommendations for the effective use of SMT.

Introduction

Customer relationship management (hereafter, CRM) has become an important stream of marketing research over the past two decades. Over time, this concept has evolved from a narrow understanding of CRM as a specific technological solution to a broadly “strategic approach that is concerned with creating improved shareholder value through the development of appropriate relationships with key customers and customer segments” (Payne & Frow, 2005, p. 168). Therefore, the implementation of the CRM process has the potential to significantly increase firm performance at the stage of customer relationship maintenance (Reinartz, Krafft, & Hoyer, 2004) and to predict new product success (Ernst, Hoyer, Krafft, & Krieger, 2011). Zablah, Bellenger, and Johnston (2004) argued that approaching CRM from the capabilities perspective encourages companies to invest in new resources that enhance the effectiveness and efficiency of this process. Furthermore, previous empirical research provides evidence that investment in CRM technology enhances CRM capabilities which have a positive influence on business performance (Wang & Feng, 2012) and margin growth rate (Morgan, Slotegraaf, & Vorhies, 2009). Digital technologies are changing markets, business environments and business models (Cortez & Johnston, 2017) as well as marketing communications paradigm (Mangold & Faulds, 2009). In this context, new media technologies that offer companies new ways to reach, interact with and customize communications with customers are particularly relevant for the CRM process (Hennig-Thurau et al., 2010). The huge amount of content created and shared through social media has a major impact on consumer knowledge, attitudes and behaviors (Mangold & Faulds, 2009). Therefore, empowered customers assume a more active role in marketing exchanges by engaging in two-way interactions with businesses and other customers.

Using social comparison theory, the purpose of this study is to examine how service employees’ dress shapes employee-customer interactions and customer-brand relationship in full-service restaurants. An analysis of 437 useable customer responses collected via an online survey indicated that appropriateness of employee dress improves employee-brand congruence, which then enhances both employee aesthetic trait and enjoyable interaction. Both employee aesthetic trait and enjoyable interaction also improve the customer-employee connection. Furthermore, gratification motivation and social motivation each mediates the effects of customeremployee connection on customers’ affective commitment toward the full-service restaurant brand.

Introduction

Dress refers to modifications (e.g., changes to nails, hair, and muscular structure) and supplements (e.g., enclosures, body attachments, and hand-held objects) to an individual’s body (Roach-Higgins and Eicher, 1992). In service encounters, dress is a form of nonverbal communication (Bonaccio et al., 2016; Choi and Mattila, 2016), and the dress of a service employee directly influences customers’ expectations of a service experience (Kim and Baker, 2017; Pounders et al., 2015). Former studies have shown that not only does employee dress impact employees’ work performance and social identity (Yeh et al., 2013), but it also influences customers’ perceived value of and relationship with a service brand (Shao et al., 2004). In general, customers’ interactions with service employees provide a foundation for their evaluations of service encounters, and employees’ nonverbal communications have been shown to play a crucial role in enhancing the perceived quality of service (Sundaram and Webster, 2000). To date, however, few studies have examined the importance of employee dress in the service industry, especially as it relates to the formation of employee-customer interactions and how it influences customers’ relationship with a service brand. Most studies have looked at customers’ short-term responses to employee dress such as how it affects tipping (Jacob and Guéguen, 2014) and customer satisfaction ratings (Magnini et al., 2013). An investigation of long-term outcomes driven by employee dress, though, have not been explored in prior studies. According to service-profit chain (Homburg et al., 2009; Larivire, 2008), employee-customer interactions during service experiences may help customers develop social identity with the service company, resulting in the formation of long-term customer loyalty behavior and increasing firms’ financial performance.