Customer Relationship Research Articles

Reviewing the digital skills and readiness of hospitality and tourism graduates: a way of success

PurposeThe purpose of this study is to assess the digital skills and readiness of recent graduates from hospitality and tourism management programmes in Cyprus for job roles in the hotel industry. It seeks to identify gaps in their competencies and provide recommendations for enhancing educational curricula to better align with the evolving demands of the industry.Design/methodology/approachThe study includes 19 semi-structured interviews with graduates of hospitality and tourism management programmes.FindingsRecent graduates of hospitality and tourism management programs possess basic digital skills, including knowledge of Microsoft Office (Excel, Word and PowerPoint), email platforms and video conferencing tools (Zoom and Skype). However, there is a significant gap in their practical experience with industry-specific software, such as Opera, Fidelio, Booking.com and Expedia, which are critical for hotel operations. Graduates mentioned that those tools were only briefly covered in their academic programmes, leaving them underprepared for their application in real-world settings. Additionally, graduates expressed a need for more comprehensive training in digital marketing tools, social media management platforms and customer relationship management systems.Originality/valueThis preliminary research aims to give industry stakeholders, including educators, an initial understanding of the importance of digital skills and the readiness of hospitality and tourism graduates in this area. In countries that rely heavily on tourism but face a shortage of skilled employees, it is vital to understand the gap between what students are learning and what the industry actually needs.

Enhancing loyalty in luxury fashion with AI: the mediation role of customer relationships

PurposeThis study aims to investigate the impact of artificial intelligence (AI) on customer loyalty in the luxury fashion market. It explores how AI-driven tools influence customer trust, satisfaction, commitment and engagement, which in turn affect loyalty. By examining these relationships, the study provides insights into the acceptance and effectiveness of AI technologies in enhancing customer loyalty within the luxury fashion sector.Design/methodology/approachThis study employs structural equation modelling (SEM) to analyse data collected from 406 luxury consumers in Iran. The data was gathered using a targeted sampling procedure, leveraging DigiKala’s e-commerce platform. A comprehensive literature review informed the measurement items, and a seven-point Likert scale was used. The methodology includes confirmatory factor analysis (CFA) to assess the reliability and validity of the constructs, followed by hypothesis testing through SEM.FindingsThe study reveals that AI significantly enhances customer loyalty in the luxury fashion market by positively influencing trust, satisfaction, commitment and engagement. Satisfaction and engagement were found to be key mediators between AI and loyalty, while trust had no direct impact on loyalty. The results underscore the importance of AI-driven personalized experiences in fostering stronger customer relationships and loyalty.Originality/valueThis study is one of the first to explore the impact of AI on customer loyalty in the luxury fashion market, using a comprehensive model that includes trust, satisfaction, commitment and engagement as mediators. It extends the stimulus-organism-response (SOR) and technology acceptance model (TAM) frameworks, offering valuable insights for luxury brands on how AI can be leveraged to enhance customer relationships and loyalty.

Influence of Electronic Customer Relationship Management Strategy on Performance of Small and Medium Enterprises in Kenya

Despite the high cost of electronic customer relationship software solutions, its use can be justified as an investment in building long-term client relationships, improving customer retention, and, ultimately, boosting long-term profitability. As a result, it is critical for small- and medium-sized firms (SMEs) in Kenya to take a forward-thinking attitude and maintain their market survival by adapting to developing trends in customer relationship management. This is because the modern business setting has become exceedingly dynamic, necessitating small and medium enterprises to formulate strategies that align with the rapid evolution of technology, shifting customer demands, and intensified global competition to improve their performance. The findings indicate SMEs in Kenya are increasingly implementing relatively uncomplicated information and communication technologies to enhance their capabilities in customer communication and information management. This strategic move is aimed at gaining a competitive edge by leveraging electronic customer relationship management practices. Small- and medium-sized enterprises perceive the communication component of electronic customer relationship management as more manageable, yet encounter challenges in effectively incorporating client information into their decision-making processes. Overall, it can be observed that electronic customer relationship management implementation in SMEs is often characterized by an ad hoc approach rather than a strategic one. SMEs need to align electronic customer relationship initiatives with the overall strategic goals to enhance their overall performance.

Transforming Customer Relationship Management through Disruptive Technology: An Empirical Study on Role of Artificial Intelligence and Machine Learning

Businesses, in an effort to keep up with the changing world, are now finding new ways to connect with their customers, and Artificial Intelligence (AI) is playing a big role in this change. AI tools like chatbots and systems that predict what customers need help companies be more efficient and give faster, more personalized, and more helpful service. Al and Machine Learning (ML) make it easier for businesses to understand their customers and build trust with them. AI is also helping businesses learn more about customer behavior and it is getting possible to solve problems even before they happen. But using AI isn’t always easy. Companies need to make sure customer data is safe, use AI responsibly, and keep a balance between technology and human connection. This paper looks at how disruptive technologies like AI and ML are changing customer relationship management (CRM), the benefits it brings, and the challenges businesses face. With careful planning, AI can help businesses grow while creating better connections with their customers. A sample of 219 was collected to find the result of the study. The factors identify the impact of AI and ML on Customer Relationship Management are Personalization and Customer Experience, Data Processing and Management, Enhanced Decision-Making, and System Automation.

Relationship Process Map in services: a tool to enhance the management of relationship interactions

Valuing regular customers is key to building strong, lasting relationships. This creates loyalty and allows companies to offer personalized service and anticipate future needs. However, the available service management tools do not consider how interactions are shaped and how the information recorded during continuous and medium to long-term relationships. This article proposes a tool called "Relationship Process Map" (RPM) that aims to describe the service process, considering how the relationship is formed. The RPM tool helps manage services by depicting the company's customer relationship. It identifies the recorded actions and suggests changes to improve customer relationship management. It can be used to improve service quality management and provide a rational basis for external marketing. The RPM tool highlights that it can identify deficiencies in the service process and gaps in monitoring customer interactions, which can help develop new checking mechanisms to strengthen monitoring practices.

AI-Driven Predictive Modeling for Banking Customer Churn: Insights for the US Financial Sector

The US banking sector is operating within a very dynamic and competitive environment, providing a wide array of services under the pressure of increasingly demanding customers. Customer churn in the context of financial institutions is defined as the phenomenon of customers terminating their relationship with a bank. The central tenet of this research project was to devise and develop predictive models of artificial intelligence that can help address the issue of customer churn from the banking perspective. The dataset of banking customer churn prediction used for this analysis comprises a comprehensive set of data about customers from a leading financial institution. It includes extensive customer records, each described by features representing different dimensions of customer behavior and demographics. The three most influential algorithms were selected for this study: Logistic Regression, Random Forest, and XG-Boost. Each model has different strengths that are quite appropriate for the intrinsic complexities of the customer churn forecast. Random Forest was the best in terms of accuracy among the models, with a relative accuracy, which may indicate that this algorithm fits the underlying pattern in the data best. The integration of AI-driven churn prediction models in the US financial sector has far-reaching implications for banks, enhancing their operational efficiency and customer relationship management. First and foremost, it can identify at-risk customers with a high degree of accuracy, thus helping the banks to implement focused retention strategies that can bring down the churn rate significantly.

Integration of Customer Data Management in a Web-Based Fishing Profile Application

The advancement of communication media and technology has driven various business sectors to transform digitally, including fishing businesses in South Tangerang City. However, many fishing businesses still lack adequate information systems to manage company profiles and customer data in an integrated manner. This research aims to analyze, design, and implement a fishing profile website equipped with customer data management features using the Waterfall software development methodology. The waterfall methodology was chosen for its systematic and structured approach, which involves five main stages: requirements analysis, system design, implementation, testing, and maintenance. The process begins with requirements analysis and collecting necessary customer data to proceed to the data integration stage, followed by system design and implementation by developing a user-friendly web-based fishing profile application. System testing uses black box testing to ensure all features function properly. The research results show that the developed fishing profile website provides professional information and manages customer data, including customer registration, visit history, and service preferences for available fishing products. This system can enhance operational efficiency and strengthen fishing businesses' customer relationships. In conclusion, integrating customer data into a fishing business profile website can serve as an effective solution to support digital transformation in this sector.

Knowledge transfer in business-to-business customer relationship development

Knowledge transfer in business-to-business customer relationship development

Customer Churn Prediction Using Machine Learning

Customer attrition poses a major issue for the telecommunications sector, resulting in revenue decline and higher expenses for gaining new customers. Predicting churn accurately enables telecom companies to take proactive measures to retain customers. This study leverages specifically Random Forest, Decision Tree, and XGBoost, to develop a robust churn prediction model. These algorithms analyze customer behavioral data, including call duration, internet usage, billing history, and complaints, to identify potential churners. Decision Tree provides an interpretable model, Random Forest improves predictive accuracy through ensemble learning, and XGBoost enhances performance with gradient boosting and optimized handling of imbalanced datasets. The proposed model assists telecom companies in classifying customers based on their churn risk, enabling the implementation of targeted retention approaches like tailored discounts and rewards programs. By integrating advanced machine learning techniques, telecom service providers can enhance customer retention, minimize the churn rates, and improves the business sustainability. The study highlights the importance of data-driven decision-making in the telecom sector, demonstrating how predictive analytics can optimize customer relationship management and drive profitability. Key Words: Predicting telecom customer churn, machine learning techniques, Random Forest algorithm, Decision Tree method, XGBoost model, retention of customers, analytics for forecasting, gradient boosting techniques, telecom sector.

Influence of consumer satisfaction on brand allegiance: An empirical investigation in Pakistan's safety and luxury automobile sector.

This study aims to evaluate the influence of customer satisfaction on brand loyalty within Pakistan's safety luxury automobile sector, featuring Toyota Indus, Honda, and Suzuki as key players. Employing a quantitative approach, the research collected data from 275 customer questionnaires. The study examined the relationships between customer expectations, perceived quality, perceived value, and brand loyalty. This study contributes original insights by exploring the unique dynamics of brand loyalty within Pakistan's safety luxury automobile sector. It sheds light on the specific challenges faced by major players in this market and emphasizes the critical role of effective customer communication and the strategic use of Customer Relationship Management (CRM) data to enhance the customer experience and promote brand loyalty. These findings offer valuable perspectives in a sector integral to Pakistan's economic development. The research uncovered significant associations between customer expectations, perceived quality, perceived value, and brand loyalty. Despite their market dominance, these companies faced challenges in cultivating brand loyalty due to issues such as subpar quality, high pricing, and inadequate service. This study emphasizes the pivotal role of effective customer communication. It suggests that leveraging Customer Relationship Management (CRM) data can enhance the customer experience, ultimately fostering brand loyalty. These insights are particularly relevant in the context of a sector that plays a crucial role in Pakistan's economic development.

The Role Of Technology In Simplifying Operations To Strengthen Customer Relationships In The Culinary Industry

With the advancement of technology, the culinary industry continues to evolve. Technology not only makes businesses easier to run, but it can also strategically help enhance customer engagement. The purpose of this research is to determine the role of technology in streamlining operations and strengthening customer relationships in the culinary industry. Business operators can optimize efficiency, reduce costs, and enhance customer experience by using online ordering applications, digital inventory management systems, and social media platforms. This study also discusses the implementation of digital payment systems and the use of data analytics to understand customer preferences. The research results show that the effective use of technology can increase customer satisfaction by up to 25% and operational efficiency by up to 30%. Thus, technology is not just a helpful tool, but also a catalyst for building a competitive culinary business. Technology offers many opportunities to make culinary businesses easier and enhance customer engagement. Research results show that the adoption of the right technology can provide significant efficiency in business operations, such as cost reduction, improved service speed, and better data management. In addition, technology also plays a crucial role in enhancing customer experience through personalization, ease of access to information, and more interactive interactions. Thus, the strategic use of technology can be the key to the success of culinary businesses in the digital era, creating more efficient operations and more engaged customers. Keywords: Technology, Customer Engagement, Culinary Industry, Digital Transformation, Business Efficiency.

Digital capabilities of SMEs: driving the Industry 4.0 revolution and measuring its innovative effects

PurposeThis study developed a theoretical model to test the relationship between digital capability and Industry 4.0 (I4.0) and its effect on innovation performance in small and medium-sized enterprises (SMEs).Design/methodology/approachThe proposed theoretical model was evaluated using partial least-squares structural equation modeling and fuzzy-set qualitative comparative analysis. The data were obtained from a sample of 536 SMEs in Chile.FindingsThe proposed model presented two dimensions of digital capability: management and information and communication technologies (ICTs). Management models composed of enterprise resource planning and customer relationship management systems are essential for optimizing organizational management. Meanwhile, ICTs facilitate the smooth flow of information within an organization, leading to improved efficiency in production processes. I4.0 is encouraged by exposing SMEs to base technologies such as data analytics. These results confirm that I4.0 influences innovation performance.Practical implicationsSME managers should encourage the development of digital capabilities to transition toward I4.0, as this can make SMEs more competitive and innovative in changing and dynamic scenarios.Social implicationsI4.0 adoption and the development of digital capabilities can directly affect employment and national economic growth.Originality/valueMost studies focus on the organizational factors affecting SMEs’ I4.0 adoption. They do not, however, address the role played by current digital capability in I4.0 technology adoption and its effect on firms’ innovation performance.

The Role of Customer Satisfaction in Moderating the Effect of Brand Image and Service Quality on Loyalty

This study examines the factors that influence customer loyalty at Islamic banks in West Java in the face of increasingly fierce competition in the Islamic banking industry. The research focuses on brand image, service quality, and customer satisfaction, highlighting the moderating role of customer satisfaction. The uniqueness of this study lies in the in-depth exploration of how customer satisfaction serves as a moderator that strengthens the relationship between brand image and loyalty in the religious preferences of the people of West Java. Data was collected from Islamic bank customers in West Java using purposive sampling method, with a total of 259 respondents. Data analysis was conducted using Structural Equation Modeling (SEM) with AMOS software version 24. The results showed that brand image, service quality, and customer satisfaction have a positive and significant effect on loyalty. In addition, customer satisfaction moderates the relationship between brand image and loyalty, strengthening customer trust and long-term commitment. This research introduces a new perspective by integrating the religiosity dimension as an intrinsic factor that influences the effectiveness of Islamic banks' strategies in increasing customer loyalty. The practical implication is that Islamic banks should enhance customer experience through specific strategies, such as providing intensive training to improve employees' service skills, using technology to ensure service efficiency and convenience, and developing marketing campaigns that are consistent with Islamic values. In addition, proactive and transparent complaint management can strengthen customer relationships. These measures are important to strengthen brand image, improve service quality, and foster loyalty in the long run.

Marketing Strategy Via Instagram at Hotel Holiday Inn Express Jakarta International Expo

Purpose: This study aims to analyze the room marketing strategy of Holiday Inn Express Jakarta International Expo Hotel using social media. Method: The research employs a qualitative approach, utilizing primary and secondary data. Data collection methods include literature reviews, interviews, and field observations. Descriptive qualitative analysis was used to interpret the findings. Result and Discussion: Observations of the hotel’s Instagram account demonstrate the effectiveness of social media as a marketing tool. Instagram’s billion active users provide extensive promotional opportunities, allowing businesses to engage audiences through images, videos, and stories creatively. Influencers are critical in building trust and expanding product reach, while official accounts manage brand visibility and customer relationships. Instagram Highlights effectively organize and present key messages, fostering cohesive brand narratives. The strategic use of Instagram at Holiday Inn Express Jakarta International Expo emphasizes visuals, personal connections, and guest engagement, proving its effectiveness in boosting brand visibility and enhancing promotional efforts. Implications: The marketing strategies for Holiday Inn Express Jakarta International Expo Hotel involve enhancing product quality and service offerings to increase occupancy rates and revenue. Online marketing, mainly through platforms like Instagram, has become crucial in the hotel’s marketing mix. This involves using electronic media, such as computers and the Internet, to execute digital campaigns effectively. The findings highlight the need for thorough preparation and strategic execution in digital marketing to ensure success in a highly competitive environment.

Importance of ethical behavior in sports management

This dissertation explores the critical importance of ethical behavior in sports management, delving into how it shapes trust, compliance, and stability in sports management relationships. Ethical conduct, characterized by integrity, truthfulness, and commitment to moral values, is positioned as a fundamental pillar for maintaining a positive reputation and fostering long-term customer relationships. The study highlights the negative repercussions of unethical practices, including reputational damage, legal consequences, and financial losses. It highlights the importance of trust in forming strong sports management relationships and the legal consequences of unethical behavior in sports. Additionally, the study explores how organizational culture affects ethical behavior, the role of ethics in subordinates well-being and motivation, and the wider consequences of ethical practices in relation to corporate social responsibility goals. Using qualitative research methods, this study seeks to offer an in-depth insight into the ethical dilemmas encountered by sports professionals, the impact of leadership and organizational policies on ethical decision-making, as well as the various advantages of maintaining ethical conduct in sports settings

Integrasi Teknologi IoT pada Sistem CRM untuk Meningkatkan Kepuasan dan Retensi Pelanggan

The Internet of Things (IoT) has become one of the leading technologies in digital transformation, including in customer relationship management (CRM). This article discusses how IoT integration in CRM systems can improve customer satisfaction and retention through real-time data collection, service personalization, and data-driven decision making. With a literature study and implementation analysis, this research shows that IoT technology can provide deeper insight into customer behavior, improve operational efficiency, and create a more satisfying customer experience.

Persepsi Konsumen terhadap Transparansi Biaya Perbankan dan Pengaruhnya terhadap Pengelolaan Risiko Keuangan Bank

This study aims to examine the impact of banking fee transparency on financial risk management in Banyumas Regency. Focusing on five main variables—clarity of fee information, ease of information access, perceived fairness, customer satisfaction, and technological systems—the research involved 116 respondents utilizing digital banking services. A quantitative approach using survey methods was employed to identify causal relationships between independent and dependent variables. The analysis revealed that fee transparency significantly influences consumer trust and loyalty, which, in turn, affects the effectiveness of financial risk management. Ease of information access, customer satisfaction, and technological systems positively and significantly impact financial risk management. Conversely, perceived fairness of fees showed no significant influence. Simultaneously, the five variables collectively contributed significantly to supporting financial risk management. This study highlights the importance of information transparency and technological innovation in creating an inclusive, trustworthy, and sustainable banking system. The findings provide insights for financial institutions to design strategies that strengthen customer relationships and for regulators to develop policies promoting transparency and consumer protection. These efforts are expected to enhance public trust in the banking system and support overall financial stability.

E-commerce and Consumer Behavior

This dissertation examines consumer behavior in the realm of e-commerce, exploring the factors that influence online purchasing decisions and strategies that enhance customer engagement and loyalty. The rise of e-commerce has dramatically shifted consumer behavior, necessitating a deeper understanding of digital shopping dynamics. Through a mixed-method approach combining surveys, interviews, and data analysis from e-commerce platforms, this study investigates key elements like personalization, content marketing, loyalty programs, and trust-building factors. The findings reveal that personalized interactions, quality content, efficient customer service, and transparent policies significantly impact customer loyalty and engagement. The research contributes to the evolving discourse on e-commerce consumer behavior, offering actionable insights for businesses seeking to optimize their online strategies. This study highlights the importance of adapting to digital consumer preferences and leveraging technology to foster long-term customer relationships in the ever-evolving digital marketplace. The research also reveals the impact of social media and influencer as the key drivers for consumer perception and buying behavior. Moreover, it notes that the use of both AI-driven recommendations and customer-generated content can provide even a higher level of user engagement and practically build the consumers’ trust in the brand. Finally, the research calls for the adoption of omni-channel approach, where the channel planning is much about a consistency to meet customers’ needs from online to the physical world.

Risk-Based Investment Planning In Biotechnology: The Business Case For Halal Detection Kit Production

This research aims to develop a new business model canvas to support PT XYZ's strategic plan in planning investment in the production of halal detection kits based on real-time PCR. The nine blocks of the business model canvas are used as a framework to evaluate the running business model, identify market opportunities, and design a business model that can optimize the potential of the halal market in Indonesia, which continues to grow. The results show that the optimization of elements, such as value proposition, key activities, key resources, customer relationships, cost structure, and revenue streams can support PT XYZ's transformation from distributor to manufacturer. The development of this new business model is expected to improve operational efficiency, maximize the potential of the local market, and create innovative and sustainable products. This research provides a strategic foundation for companies to take advantage of opportunities in the halal industry while increasing competitiveness through collaboration and adoption of modern technology in supporting value-based business development for the halal industry.

Information Disclosure of Electronic Commerce in Vietnam: Expectancy and Social Contract Theory Perspectives

This study investigates the sequential relationships among motivations for online information disclosure, willingness to disclose and purchase behaviours on e-commerce platforms. The expectancy theory of motivation and social contract theory provide the theoretical basis, interpreting how anticipated disclosure outcomes and perceived fairness in the exchange process impact willingness to disclose and subsequent purchase decisions. This study employed a quantitative research approach with three sampling methods (e.g., purposive sampling, quota sampling and snowball sampling). The mass survey was distributed to students from five universities located in Ho Chi Minh city and Ha Noi capital, the two largest e-commerce markets in Vietnam. There were 695 valid cases used for theoretical estimation by using partial least squares structural equation modelling. Three driven forces of information disclosure were identified (e.g., flow experience, perceived information relevance and trust in platform), while the perceived Internet competency negatively impacts willingness to disclose. In turn, willingness to disclose had a significantly positive impact on online purchase behaviour. The study suggests that the behavioural and contextual factors causing online disclosure should be interpreted to design effective disclosure regulations and norms. It’s crucial for business providers to promote a sense of fairness and build strong customer relationships to enhance user decision-making.