Service Industry Research Articles

The Development of the Outsourced Facility Service Market in the EU

The Facility Service (FS) industry lacks comprehensive scientific reports due to its fragmented representation in the NACE industry classification system in the EU. This article addresses this gap by offering insights into the FS market's turnover, number of companies, and employees. The study examines the development of turnover, company count, and employee numbers in the outsourced FS sector in the EU and the five major European economies since 2008. The European norm EN 15221:4 defines FS activities, which were cross-referenced with Eurostat's economic data to identify relevant FS services. Extensive data quality checks were conducted to ensure accuracy. From 2008 to 2018, the FS sector's size in terms of turnover and companies was estimated and compared across countries. Findings reveal that the EU's FS sector reached a turnover of over 1142 billion in 2017, with nearly 2 million companies and over 15 million employees. Despite the 2008/2009 financial crisis, the FS sector in the EU demonstrated stability compared to the broader economy in the selected countries.

Modeling price-sensitive demand in turbulent times: an application to continuous pricing

AbstractPricing drives demand for service industries such as air transport, hotels, and car rentals. To optimise the price, firms have to predict real-time customer demand at the micro level and optimise the price. This paper contributes to revenue management by introducing a nonparametric statistical approach to predict price-sensitive demand and its application to continuous pricing. Continuous pricing lets service companies maximise revenue by using customers’ willingness to pay. However, it requires accurate demand estimations, particularly of customers’ price sensitivity. This paper introduces an augmented generalised additive model to estimate price sensitivity, which identifies substantial variations in price sensitivity, exceeds the predictive performance of state-of-the-art alternatives, and controls for price endogeneity. In addition, the demand model has variable price derivatives enabling continuous pricing. The proposed approach offers a simple and efficient way to implement continuous pricing with a closed-form solution. Our research also highlights the relevance of considering the problem of price endogeneity when estimating price-sensitive demand based on observations from prior pricing decisions. We demonstrate how continuous pricing is applied using empirical airline ticket data. We document a field study, which shows a revenue increase of 6% on average, and outline how the approach applies to turbulent market conditions caused by the COVID-19 pandemic, the surge in inflation since mid-2021, and the start of the Ukraine war in April 2022.

How do you treat your ‘big fish’? The joint effect of perceived subordinates’ overqualification and managers’ personalities on knowledge hiding

ABSTRACT By integrating the cognitive appraisal theory of stress and coping and the conservation of resources theory, this paper explores the interactions and the mechanism of perceived subordinate’ overqualification and personalities on managers’ knowledge hiding in the service industry. Using a multi-stage research design supported by data collected from upscale hotels in China in three waves (n = 453), the results suggests that when perceiving subordinates’ overqualification, managers with highly cooperative personality decrease knowledge hiding. Conversely, managers with highly competitive personality increase knowledge hiding. Moreover, self-protection motivation mediates the positive relationship between perceived subordinates’ overqualification and managers’ knowledge hiding. This study not only contributes to a better understanding of the psychological mechanism of managers’ knowledge hiding but also responds to the call for multilevel effects research on overqualification. The study’s findings can also serve as important references for hotels’ human resources practices to maximize the values and contributions of human capital.

Towards sustainability in the services industry: Does green top management support stimulate an organization's green operational performance? A moderated mediation model

Towards sustainability in the services industry: Does green top management support stimulate an organization's green operational performance? A moderated mediation model

Is There a J-Curve Effect in the Korean Service Trade?

ABSTRACT In this article, we test the asymmetric J-curve hypothesis using data from 10 Korean service industries. When we tested for a symmetric J-curve using the linear autoregressive distributed lag (ARDL) approach, we found support for the J-curve in one industry and the inverse J-curve in two industries. However, when we tested the asymmetric J-curve using the nonlinear ARDL approach, we found support for the asymmetric J-curve in four industries and the asymmetric inverse J-curve in four more industries. The increase from three to eight cases is attributed to the nonlinear adjustment of the real effective exchange rate of the won.

Optimizing autonomous navigation in unknown environments: A novel trap avoiding vector field histogram algorithm VFH+T

The Vector Field Histogram Plus (VFH+) algorithm is a cornerstone in robotic navigation, renowned for its efficiency and straightforward implementation across a multitude of environments. Despite its widespread utility, the algorithm's inherent limitations in handling complex obstacle entrapments necessitate refinement. This paper presents an advanced iteration, designated as VFH + T, which incorporates sophisticated memory-based trap recognition and avoidance mechanisms. This enhancement facilitates dynamic adjustment of navigation strategies through the integration of geometrical rules that retrospectively inform path planning decisions. Moreover, the VFH + T algorithm intricately melds the robotic platform's kinematic and dynamic constraints, optimizing real-time navigational commands based on both current sensory input and historical environmental interactions. Empirical simulations validate the enhanced algorithm's proficiency in circumventing navigational traps, improving operational safety and efficiency. Comparative analysis with VFH+ and VFH* algorithms show up to 17 % reduction in traveling distance due to the trap-avoidance technique during navigation. This advancement holds significant implications for enhancing autonomous navigation technologies in various practical applications, from self-driving vehicles to robotic aids in logistics and service industries.

A comparative experimental research on the diagnosis of tooth root cracks in asymmetric spur gear pairs with a one-dimensional convolutional neural network

Gearboxes transfer rotational motion and handle precision functionalities in many fields, including aviation, wind turbines, and industrial services. Their health management is essential to minimize workforce risks, increase the level of safety, and avoid machine breakdowns. From this standpoint, the present experimental research work developed a convolutional neural network-based method for diagnosing different levels of tooth root cracks (25 %-50 %-75 %-100 %) for symmetric (20°/20°) and asymmetric (20°/30°) profiled gear pairs. A series of vibration experiments were performed on a one-stage spur gearbox to achieve this by using a tri-axial accelerometer under variable working loads. The main purpose of this experimental research study is to explore the influence of the tooth profile on spur gears’ vibration responses and whether utilizing an asymmetric tooth profile would positively impact a deep learning algorithm's classification accuracy to add to the enhancements it provides in terms of fatigue life, mesh stiffness, and impact strength. Experimental results revealed that the overall classification accuracy could be increased by 7.712 % by feeding the proposed deep learning model with vibration data measured using test samples with asymmetric teeth.

Diffusion of AI value-driven services in the German manufacturing industries—an empirical examination of value-driven service references classified by the business Model Canvas

Diffusion of AI value-driven services in the German manufacturing industries—an empirical examination of value-driven service references classified by the business Model Canvas

Investment Advice of Dialysis Companies: Whats the Trend of the Industry?

The global dialysis market is continuing expanding in the recent years and dialysis industry has expected investment prospects. This study presents a comprehensive investment analysis framework comparing four top companies in the kidney care and dialysis service industry. This article aims help investor choose the most suitable company among them with the highest investment value to invest in. The study uses official financial data from Nasdaq from 2023 and forecast data from estimates of 2024 of 4 dialysis companies on the waiting list. By analyzing and comparing the financial statements of four companies, the asset investment potential and growth rate of the four companies were determined. Results demonstrate that the company DaVita rank as the most appealing investment option out of four companies, followed by Medtronic, Baxter and Fresenius. Based on financial statements, DaVita is attractive with highest expected growth rates in EPS and gross revenue, PEG ratio, and relatively high annual and quarterly gross margin.

The Influence of Mobile Application User Experience, Service Quality, and Social Interaction on Customer Satisfaction Quantitative Research in the Online Service Industry

The Influence of Mobile Application User Experience, Service Quality, and Social Interaction on Customer Satisfaction Quantitative Research in the Online Service Industry

Revolutionizing defect recognition in hard metal industry through AI explainability, human-in-the-loop approaches and cognitive mechanisms

Defect detection is one of the main areas that Industry 4.0 concepts like automation, IoT, digitization and AI aimed to provide solutions. In this work, a platform that extends the aforementioned concepts with ones coming from Industry 5.0 like reconciliation and collaboration between humans and machines is introduced. The proposed platform provides defect detection and localization services for hard metal industry by extending current AI solutions with exponentially growing technologies such as interpretable and explainable AI (XAI), human-in-the-loop (HITL) approaches and cognitive retraining mechanisms. In particular, the platform, that is built on a micro-service architecture to enable its software sustainability, is powered by machine and deep learning models for defect detection and localization. These models are able to recognize the defects, locate them with high precision and present them to end users so to maximize resiliency in quality inspection processes. Alongside the state-of-the-art AI algorithms that are utilized by the platform, the human in the loop mechanisms and interfaces that enable human experts to inject their knowledge for AI models training are considered as key innovative aspects of this work. To enhance further the human and AI collaboration, XAI mechanisms are included in the platform,to enable the experts to gain useful insights regarding the operation of the AI models in order to be able to provide further feedback that can trigger on-the-fly platform’s cognition mechanisms to improve models’ accuracy and performance.

PENGARUH KINERJA KEUANGAN, STRUKTUR MODAL DAN UKURAN PERUSAHAAN TERHADAP NILAI PERUSAHAAN MELALUI KEBIJAKAN DIVIDEN INDUSTRI JASA SEKTOR KEUANGAN TBK PERIODE 2020 - 2022

This research aims to test and analyze the significant influence of financial performance, capital structure and company size on company value through the dividend policy of the Tbk financial services industry for the period 2020 - 2022. This research uses an explanatory research type of research using a quantitative approach. The sampling technique used the purposive sampling method, a sample of 21 financial sector service industries was obtained from a total population of 51 financial sector service industries. The type of data in this research is secondary data. Data obtained from the official website of the Indonesia Stock Exchange in the form of annual financial reports from the financial sector services industry for the period 2020 - 2022. Data analysis was carried out using descriptive statistics with the SmartPLS tool. Based on the results of data analysis, it shows that financial performance, company size and dividend policy have a positive and significant influence on company value, capital structure has no effect on company value. Financial performance, capital structure and company size have a positive influence on dividend policy. Financial performance, capital structure and company size have a positive influence on company value through dividend policy.

Assessing the effect of digital platforms on innovation quality: mechanism identification and threshold characteristics

In the digital era, digital platforms are gradually changing the ways of life and social production and are becoming the centre of digital services in various industries. Additionally, they break the established institutional framework of social recognition and promote technological change and innovation. Thus, examining the quality of innovation facilitated by digital platforms has become an important area of research. This paper utilises China’s 2011–2021 provincial panel data and examines digital platforms, resource mismatches and innovation quality within the same research framework. The direct, indirect and nonlinear effects of digital platforms on innovation quality are explored using the fixed effects model, intermediary effect model and dynamic threshold regression model. The findings indicate that digital platforms have a significant positive direct effect on innovative quality, and resource mismatches play intermediary and threshold roles in the process. These findings offer policy guidance for constructing robust digital platform ecosystems and enhancing innovation quality.

A fine-grained investigation on the predictors of urban green space growth in Nanjing

ABSTRACT Existing studies have primarily examined urban green space (UGS) evolution in isolation from the urban development context, neglecting the dynamicity of the factors affecting UGS growth in different spatiotemporal conditions and urban development levels. Taking Nanjing as the study site, we constructed spatial lag models using multi-source data and investigated the patterns and predictors of UGS growth across diverse spatiotemporal conditions in high-density environments. The model results show that: (1) although good natural conditions can support UGS development, this effect is greatly weakened in fast urban expansion as other land uses show higher priority in land occupation; (2) industrial and public service lands and commercial lands show a negative effect on UGS growth in the early and late urbanization, respectively, while residential lands demonstrated sustained negative effect in all the urbanization phases; (3) the effect of the total population and population structure varies in different urban development phases; (4) at an advanced urban development level, the areas close to city centre have better opportunities to install new UGSs. These findings offer useful references to the decision makers and planners, especially for their work on the UGS layout optimization within the high-density areas.

The Guidelines for Enhancing Knowledge and Proficiency in Food Decoration Skills: RMUTP

The purpose of this study was to examine the level of knowledge and skills related to food decoration, and to identify consistent study activities for each academic year in the food service industry's student program through correspondence analysis. The population was 304 people. The results demonstrated a high level of knowledge and behavioral learning in the area of artistic skills. An analysis of the correlation between the academic year and activities aimed at enhancing knowledge, skills, and creativity in the art of food decoration revealed that the 1st year students engaged in activities related to analyzing food decoration design, the 2nd year students focused on the fundamentals of food decoration, the 3rd year students explored visual elements and art principles in food design and decoration, and the 4th year students assessed their ability to design food decorations before class. Activities to enhance art skills involved 1st year students participating in exhibitions, 2nd year students participating in artificial decoration activities, and 3rd and 4th year students participating in culinary workshops and learning about food decoration techniques. Activities to enhance creativity involved the 1st and 2nd students creating images from points, the 3rd students participating in art camp activities, and the 4th students learning how to add value to food through plating and photography.

Policy Learning and the Diffusion of Autonomous Vehicle Policy in the American States

This study examines the multifaceted mechanisms driving the adoption of autonomous vehicle (AV) policy in the United States. Drawing from diffusion and network governance theories, it explores the intricate interplay between state governments, private industry, and shared mobility services in shaping AV policies. Several states like California, Nevada, and Texas have emerged as frontrunners in AV testing and innovation. However, policymakers grapple with unique challenges related to AV technology, including safety, liability, and infrastructure enhancement, necessitating innovative policy solutions. As AVs signify a transformative shift in transportation, state governments assume a pivotal role in policy innovation and experimentation. Using a blend of dyadic quantitative analysis and qualitative interviews, this study examines to what extent policy learning predominantly drives AV policy adoption. In doing so, we explore specific diffusion mechanisms, including policy learning and competitive dynamics, to understand how they shape the early adoption of AV policies across states. We find substantial evidence for interstate learning facilitated by intergovernmental organizations and the private sector.

How Does Internationalization Help Reputation? The Role of the Learning Gap

This study delves into the intangible effects of internationalization on reputation, and proposes a mechanism by which internationalization can lead to improved reputation. Grounded in institutional and signaling theories, we begin by proposing that internationalization signals learning advantages deriving from experience in host environments and responses to foreign institutional pressures. Then, we derive the learning gap construct from two principal dimensions of the diversity of location portfolio, namely home—host cognitive distance and power asymmetry; and posit that this learning gap explains the link between internationalization and reputation. Analyses based on the legal service industry demonstrate that while international diversification is important in predicting reputational benefits at home, its effect is mediated through the learning gap deriving from each firm's internationalization, underscoring potential advantages of home—host differences.

Factors influencing luxury service brand extension in a developing country

PurposeDespite the prevalence of luxury brand extension in the service industry, customers tend to be skeptical of the value of the extended brand. This study aims to investigate whether a parent luxury service brand significantly alters customers’ predicted quality, identity and attitude toward the extended brand.Design/methodology/approachThis study uses partial least squares structural equation modeling to examine the proposed hypotheses in a developing country.FindingsThe results show that the parent brand’s brand distinctiveness positively and significantly signals the identity and quality of the extended brand. The model also identifies the mediating effects of quality as it signals the relationship between customers’ perception of the parent brand and attitude toward the extended service brand. As expected, as the quality of the extended brand improves, so does attitude toward the extended hotel brand. By contrast, the perceived identity of the extended brand does not significantly increase support for a positive attitude toward the extended brand.Originality/valueThis study contributes to the existing consumer marketing literature by suggesting future research directions and brand extension strategies for luxury hotel brand companies in developing countries.

Unveiling Excellence in Service: from Exceptional Staff to Exceptional Guest

This research aim at exploring excellence service in hospitality industry. The research method was deep interview with the management of AH hotel and resort. The focus was unveiling service excellence on the pivotal role of exceptional staff in catering to the needs of exceptional guests. Drawing upon literature on service excellence, staff engagement, and guest satisfaction, the abstract highlights the importance of personalized experiences and genuine dedication in surpassing guests' expectations. The result were through a commitment to understanding guests' preferences and fostering a culture of excellence among staff, hotels can elevate the guest experience and cultivate long-term loyalty. The uniqueness of excellence service at the accounting department lies in its precision, efficiency, personalized financial solutions, proactive management, and transparent communication, all of which contribute to a seamless guest experience and the hotel's success. The symbiotic relationship between excellence staff and excellence guests in the pursuit of service excellence. Hotel management is advised to constantly remind employees about the importance of maintaining service quality to avoid complaints from management, colleagues, and hotel guests.

Impact of Branding on Consumer Behaviour at Himalayan Java Coffee Shops in Kathmandu Valley

The study examines how branding affects consumer behaviour of consumers visiting Himalayan Java Coffee Shops in Kathmandu Valley by assessing the mediating effect of consumer attitude in relation to the branding elements (brand image, brand loyalty, brand trust and brand experience). The cross-sectional data was purposefully collected from 208 respondents ranging from under 18 years to older people residing in the Kathmandu Valley and previously who are exposed to consumption of coffee. Primary data was analysed quantitatively by using SMART-PLS. The study findings indicated significant impact of the constructs – Brand Image, Brand Loyalty, Brand Trust and Brand Experience on consumer behaviour at Himalayan Java. Additionally, the structural model affirmed that consumer attitude would act as a mediator in the relationship between Brand Image, Brand Loyalty, Brand Trust and Brand Experience. By filling in empirical gaps and utilising Theory of Planned Behaviour (TPB), this study advances our knowledge of how Brand Image, Brand Loyalty, Brand Trust and Brand Experience impacts consumer behaviour especially in case of Himalayan Java. The study stresses the eminent role of branding that impacts the consumer behaviour with the potential to assist the managers of several service and manufacturing industries to consider various branding elements when reaching out to the customers.