INTRODUCTION
Background and necessity of the research
1.1.1 Why improving productivity is important in Vietnam context?
Productivity is crucial for enhancing the competitiveness of firms and nations in an increasingly integrated global market By boosting productivity, societies can increase the output of goods and services, which is essential for improving national competitiveness and fostering international relations and cooperation (Te & Dong, 2013) For developing countries like Vietnam, enhancing productivity is vital for achieving rapid and sustainable growth, moving beyond middle-income status, and keeping pace with regional counterparts.
In 2018, Vietnam's labor productivity growth rate reached 6%, with an increase of 5.77% from 2016 to 2018, according to the Vietnam Government Office (2019) The labor productivity per worker was reported at 4,521 USD, while the GDP per worker, as calculated by APO (2019), stood at 9,300 USD using 2017 constant prices and 2011 purchasing power parity Despite these figures, Vietnam's productivity remains lower than that of other Southeast Asian countries.
Figure 1.1: Productivity of Vietnam and some other countries in 2018 (Source: Vietnam
1.1.2 Why productivity improvement in hotel industry of Vietnam is necessary?
The hotel industry is crucial for achieving Vietnam's long-term development goals, yet the country's productivity remains low compared to Southeast Asia and Asia as a whole Specifically, Vietnam's tourism productivity lags significantly behind its regional counterparts, achieving only 40% of Thailand's and 45% of Malaysia's levels In 2017, labor productivity per worker in the tourism sector was just 77 million VND (approximately 3,400 USD) (Hoang et al., 2019).
In the Vietnam Tourism Annual Report 2019, the Vietnam National Administration of Tourism reported an average room occupancy rate of 52 percent, down from 54 percent in the previous year This decline may be attributed to a faster increase in accommodation supply compared to demand, along with shorter tourist stays Notably, areas experiencing rapid growth in tourist accommodations, such as Da Nang, have reported hotel occupancy rates falling below 50 percent in some instances.
The COVID-19 pandemic significantly disrupted the Vietnamese hotel market, leading to substantial losses for hotels, tour providers, and travel agencies, as reported by CBRE (2020) With the inability to reach break-even points, the industry faced unprecedented challenges.
Productivity of Vietnam and some other countries in 2018 (calculated in USD by PPP
Several hotels have resorted to reducing staff working hours, laying off employees, and ultimately closing temporarily due to the impact on tourism The Vietnam National Administration on Tourism (VNAT) estimates that Vietnam's tourism sector has experienced significant losses, as reported by CBRE.
$5.9-$7.7 billion in the month of February – April 2020
Understanding the determinants of productivity improvement in the hotel industry is crucial, as enhancing productivity allows hotels to gain a competitive edge in the market.
1.1.3 Research about productivity improvement in hotel business
Research has shown that various factors significantly influence productivity levels globally Key elements identified include advancements in scientific and technological development, the quality of human capital, effective production management practices, and supportive policies, all of which play a crucial role in enhancing labor productivity (Dong & Shi).
Research indicates that while environmental management negatively impacts labor productivity, quality management positively influences it (Frondel et al., 2018; Ma et al., 2020) Most studies have concentrated on productivity factors within the manufacturing and construction industries (Alaghbari et al., 2017; Munyai et al., 2017; Chaturvedi et al., 2018; Wong et al., 2020) or examined how leadership styles affect labor productivity (Zehir & Narcikara, 2016; Yan, 2018; Olanrewaju et al., 2020).
Research on productivity improvement factors in the tourism sector is less extensive compared to the manufacturing and construction industries Most studies focus on the effects of market segmentation, leadership styles, and management approaches (Joppe & Li, 2014; Witt et al., 2010) Additionally, other research has explored how employee-employer relationships and workforce flexibility influence labor productivity (Mill, 2008; Simpao, 2018).
Recent research in Vietnam has focused on the impact of various factors on labor productivity within the construction industry (Te & Dong, 2013; Huynh & Le, 2016) Additionally, studies in the tourism and hospitality sector have emphasized methods for measuring and calculating service productivity (Hoang et al., 2019; Loan et al., 2009).
Research on the factors influencing productivity in the tourism sector is essential for advancing the hospitality industry To accurately identify the determinants of productivity improvement, careful selection of survey samples and subjects is crucial Due to time and geographical limitations, this study focuses on hotels in Da Nang city, Vietnam, recognized for its accolades such as being the most livable city in Vietnam and one of Asia's top 10 attractive destinations With its diverse range of hotels in terms of ownership, star classification, and operational years, Da Nang provides a representative sample for this research, reflecting the vibrant tourism landscape that attracts millions of visitors annually.
Based on the research gap in Vietnam and in the world, as well as from the practical needs of improving labor productivity in Vietnamese, the author chooses the topic:
“DETERMINANTS FOR PRODUCTIVITY IMPROVEMENT IN HOTEL
BUSINESS: THE CASE OF DANANG, VIETNAM” as thesis research.
Aims of research
The research titled "Determinants for Productivity Improvement in Hotel Business: The Case of Danang, Vietnam" aims to explore how factors such as waste reduction, process management, innovation, technology application, and customer focus influence productivity in the hotel sector Additionally, it examines the mediating effects of employee and customer satisfaction on productivity enhancement Based on the analysis findings, the author will suggest various solutions to boost productivity and enhance competitiveness in the industry.
• To review the previous researches about productivity in the hotel sector n
This study investigates how various factors, including waste reduction, process management, innovation, technology application, customer focus, employee satisfaction, and customer satisfaction, directly and indirectly influence productivity improvements within the hotel sector.
• To propose solutions to improve the productivity of the hotel sector.
Research questions
• What factors related (both direct and indirect effect) to hotel productivity improvement?
• How the factors have a direct and indirect impact on productivity improvement in the case of Danang's hotels?
Research scope
The study was conducted for hotels in Danang city Information was collected from reports, handbooks, etc., and collected data through surveys between May 2020 and September 2020.
Process and methodology
This research builds upon previous studies to establish a research model, followed by the collection of primary data from hotels in Danang The analysis of this data is conducted using SPSS 16 and AMOS 24 software Additionally, secondary data regarding labor productivity in Vietnam's service sector is gathered from relevant reports.
Data collection will involve a pencil-and-paper survey, utilizing a 5-point Likert scale for all questions Additionally, secondary data will be gathered from various sources, including policies and reports, to provide essential background information.
Data is coded, screened, and analyzed on the statistical software as following steps:
Chap 1: Literature review Chap 2: Research methodology
Chap 3: Analysis Chap 4: Finding and conclusion
LITERATURE REVIEW
Concepts of productivity
Productivity is a multifaceted concept that varies based on context, as highlighted by Tangen (2005) Alaghbari et al (2017) support this notion, suggesting that researchers should adopt diverse perspectives on productivity due to differing methodologies This leads to a wide array of productivity definitions, as noted by Oglesby et al (2002) and Lema (1995) Tangen and Alaghbari et al provide a comprehensive review of these various definitions of productivity.
• Peles (1987) defined productivity as "operation performance," whereas Handa and Adballa (1989) defined productivity as the ratio of outputs of commodities and/or services to inputs of fundamental resources
Productivity involves maximizing resource efficiency by generating a greater number of items from the same inputs or achieving the same output with fewer resources (Bernolak, 1997).
• Furthermore, Arditi and Mochtar (2000) advocated calculating productivity as total outputs in dollars divided by total inputs in dollars
• Productivity is defined as the efficiency with which components of production, labor, and capital create value (Bheda et al., 2003)
Productivity is a fascinating area of research with various definitions Te and Dong (2013) define productivity as a measure of labor efficiency in the production process, comparing output indicators with the labor required for their creation Some scholars argue that productivity encompasses complexity factors, necessitating the inclusion of labor inputs and outputs in its definition Quyen (2014) categorizes productivity into two types: individual productivity, which refers to the performance of a single worker, and societal productivity, which reflects broader economic contributions.
Productivity is quantified by the ratio of completed output to the time invested in producing goods Social productivity, an essential component of national statistical indicators, is assessed through the average GDP per employee within a given year This concept reflects the overall efficiency of a country's labor force, illustrating the effectiveness of all resources utilized within a company or society.
Productivity is commonly defined as the ratio of output to input, representing the relationship between goods and services produced (output) and the resources utilized (input), such as labor and capital This relationship can be expressed with the formula: Productivity = Output / Input Understanding productivity in this way allows for a clearer assessment of efficiency in various processes.
In 2019, APO emphasized that two key components are essential for inputs: labor and capital, which encompasses buildings, plants, and machinery Additionally, intermediary inputs such as components, materials, and energy are also considered inputs in specific contexts.
Productivity is defined as the ratio of outputs to the combinations of inputs utilized to generate those outputs, highlighting its multifaceted interpretations (Gidwani & Dangayach, 2017).
Measuring company productivity involves evaluating how effectively an organization utilizes its resources to achieve customer satisfaction by delivering products and services that align with market expectations This aspect of productivity plays a crucial role in assessing overall business performance.
APO (2019) illustrated the following way to measure inputs and outputs of productivity Firstly, APO (2019) demonstrated two metrics of popularity outputs (1)
Gross output measurement assesses the value of goods or services produced by utilizing the prices of finished outputs In contrast, the value-added metric calculates the gross output value by subtracting all expenditure items, highlighting the value added by the production process.
In the context of product acquisition, there are three primary types of input measurement: Labor, which accounts for the total hours worked by all individuals involved in the production process; Capital, referring to the flow of services derived from available capital; and Intermediates, which represents the overall value of all intermediate goods used, adjusted for price inflation.
These types of inputs and outputs lead to four available ways to measure productivity
• Labor productivity = Outputs/(Labor inputs)
• Capital productivity = Outputs/(Capital inputs)
• Intermediate productivity = Outputs/(Intermediate Inputs)
• MFP = Outputs/(Combined labor, capital, intermediates)
According to APO (2019), productivity can be measured in several ways, including Per-Worker Labor Productivity, which assesses labor productivity by calculating GDP per worker in US dollars Another method is Per-Hour Labor Productivity, which evaluates the amount of output generated per hour worked Additionally, Total Factor Productivity measures GDP relative to the combined inputs used in production.
On the other hand, Quyen (2014) proposed the main following ways to measure productivity
W: labor productivity of one labor
Q: The total number of output calculated by product
T: The total number of worked labor
Q = value-added or revenue and T = a total number of employees or total number of times (days, hours,…)
• Productivity calculated by worked time: t = T/Q t: the number of labor resources used for product (in units of time)
The hospitality sector faces challenges in measuring productivity due to the intangible nature of its services, making it difficult to objectively define and assess service outputs Additionally, the simultaneous production and consumption of hospitality services, along with their perishability and variability, complicate the evaluation of inputs and outputs The complexity of this relationship is influenced by the number of inputs and outputs and their measurement units In practice, various methods exist for comparing these factors, with ratio analysis being the most commonly used approach in the hospitality industry (Sigala, 2004).
According to Mill (2008), productivity metrics in the hotel sector primarily emphasize labor effectiveness by analyzing the ratio of outputs to inputs He suggests various methods for measuring productivity within the hotel industry.
Hotel productivity can be effectively measured through various metrics, including payroll ratio, sales per employee, sales per hour, and sales per employee-hour Research by Shaheen et al (2018) highlights that employee productivity is fundamentally the ability to meet customer demand Additionally, financial indicators such as revenue, sales, and added value provide valuable insights into employee productivity levels.
2.1.3 Productivity and determinants in manufacturing
In their study on labor productivity in the Masonry Walls project, Santos et al (2020) defined productivity as the efficiency of transforming inputs into outputs aligned with the project's objectives Conversely, Dixit and Sharma (2020) characterized productivity in construction projects as the ratio of performance outputs to the inputs used to produce them They emphasized that in the construction industry, outputs may include metrics such as weight, volume, or area, while inputs typically consist of labor, materials, and machinery.
The difference between productivity in manufacturing sector and service sector
Productivity is viewed differently across occupations, particularly between manufacturing and service industries Manufacturing productivity is easier to measure, while assessing productivity in the service sector presents more challenges This complexity arises from the intangible nature of service outputs and the various methodologies used to analyze productivity in this sector.
Service productivity differs fundamentally from manufacturing productivity due to the unique characteristics of services, such as intangibility, heterogeneity, inseparability, and perishability, as noted by Biege et al (2013) These traits hinder the effective application of manufacturing productivity calculations to services, resulting in low productivity assessments and inaccuracies The simultaneous consumption and fleeting nature of services, which are influenced by human and environmental factors, further complicate the evaluation process Additionally, Gallego et al (2015) emphasized the lack of research on service productivity, attributing it to the ethereal and interactive nature of the final product, which makes it challenging to determine service output and differentiate it from inputs in the production process.
The second feature of calculating service productivity is its diverse and multidimensional nature, making it challenging to assess as a whole Unlike physical products, where output estimation is straightforward based on easily defined quantities, service output is evaluated more flexibly Consequently, productivity measurement differs significantly between the manufacturing sector and the services sector.
Accurate measurement of productivity is essential for managing and monitoring tourism activities, particularly in Vietnam (Nguyen, 2020) However, calculating productivity in the tourism sector poses more challenges than in the manufacturing industry due to the unique nature of tourism products and services, as well as the complexities involved in determining input costs and outputs.
Service industry productivity, particularly in the hotel sector, has not kept pace with manufacturing growth (Mill, 2008) This discrepancy arises from various factors, including the lack of adoption of effective operations management strategies prevalent in manufacturing (Witt & Witt, 1989) To enhance productivity in Vietnam's tourism industry, it is essential to conduct research and develop an evaluation model to assess the current status and identify improvement solutions.
Productivity in hotel sector
2.3.1 Productivity concept in the hotel sector
Productivity is a fascinating and complicated phenomenon in the economy as a whole
Enhancing productivity in hotel and hospitality management is a challenging yet essential endeavor De Jorge and Suarez (2013) highlight that productivity in the hotel industry is measured by comparing the efficiency of service processes in converting inputs into outputs against the optimal potential for operations.
Hwang and Chang (2003) defined productivity in Taiwanese hotels using the broad term inputs/outputs, which encompassed metrics such as total guest rooms and the number of floors dedicated to food and beverage (F&B) services.
Research by Sigala (2004) highlights that productivity in the hotel industry, particularly in the rooms division, is influenced by factors such as the number of rooms, front-office payroll, administrative expenses, and demand variability, resulting in key outputs like average room rates and non-room revenue Additionally, Shaheen et al (2018) define hotel productivity in terms of employee performance, emphasizing its role in meeting consumer demand and its correlation with financial metrics such as revenue and sales Houldsworth and Jirasinghe (2006) further explore productivity by examining the relationship between managers and their employees, focusing on the effectiveness of their combined efforts.
In summary, this thesis defines productivity in the hotel sector as the ratio of inputs to outputs, highlighting the importance of efficient resource utilization in enhancing operational performance.
Inputs in the hotel industry encompass essential resources for service production and delivery, including direct raw material costs, employee numbers, and capital investments Conversely, outputs represent the results of hotel operations, such as sales revenue, profitability, market share, and competitive positioning within the industry.
2.3.2 Productivity measures in the hotel sector
In a study on tourism productivity, Blake (2006) identifies three key measures: first, output per worker, which quantifies the value each employee contributes to the organization; second, output per hour of labor, an approach that accounts for both part-time work and unused paid time, thus unaffected by overtime hours; and third, Total Factor Productivity (TFP), which assesses output relative to input units.
Analyzing productivity in the tourism service industry is more challenging than in manufacturing due to the intangible nature of its outputs and the various approaches to the issue (Hoang et al., 2019) Simpao (2018) further explores this complexity in his analysis.
Research supports the idea that labor efficiency in the hospitality industry can be assessed through various models and methods However, due to the qualitative nature of this sector, measuring outputs, particularly in terms of hotel facilities, poses challenges Inchausti-Sintes et al (2020) identified outputs per staff as a key metric for efficiency in hospitality Nevertheless, Coelli et al (2005) cautioned that relying solely on this metric may lead to misleading interpretations of a region's overall efficiency.
2.3.3 Determinants for productivity in the hotel sector
The hospitality industry has long been recognized as one of the fastest-growing sectors, significantly contributing to economic growth Numerous studies have explored the factors influencing productivity within this industry, highlighting key motivational aspects for improvement Research by Brown and Dev (1999) identifies business segment, leadership, and management style as crucial elements affecting productivity growth These findings are further supported by the studies of Joppe and Li (2014) and Witt, reinforcing the importance of these factors in enhancing the performance of the hospitality sector.
Key determinants influencing hotel productivity include external factors such as market competition, company characteristics like size and investment, business dynamics, and ownership type (public or private) (De Jorge & Suarez, 2013) Additionally, skills, human capital, physical capital, and innovation play crucial roles in enhancing productivity (Blake, 2006).
Mill (2008) identified four key factors that can significantly improve labor efficiency in the hotel industry: optimized workspace design, enhanced job procedures, flexible staff scheduling, and organizational adaptability Additionally, research by Simpao (2018) examined how labor capabilities and the dynamics between employers and employees, including promotion and incentive structures, impact labor productivity.
Park et al (2016) explored the impact of internal and external influences on competitiveness, as highlighted by Sigala (2004) Key internal factors significantly affecting productivity include the workforce size (Hu & Cai, 2004), working hours, labor flexibility (Kappa, Nitschke, & Schappert, 1997), and effective human resource practices.
(Kilic & Okumus, 2005), and labor costs (Sigala, 2004) Additionally, Inchausti-Sintes et al (2020) also confirmed that seasonality has a negative impact on going down of productivity in tourism (Basu et al., 2006; Smeral, 2003).
Productivity improvement
2.4.1 Productivity improvement in hotel sector
Improving productivity involves not just enhancing the quality of tasks but also ensuring that the right tasks are performed more effectively This improvement is a transformational process, requiring managers to facilitate and implement change across various elements, including workforce dynamics, organizational beliefs, skills and education, technology, infrastructure, products, and market strategies.
Improving productivity is essential in every enterprise to improve results (Geum et al.,
Productivity is closely linked to strategic planning recommendations aimed at enhancement (Gold, 1985; Geum et al., 2011) While productivity management is traditionally associated with mass production, much of the research has concentrated on manufacturing rather than operational aspects (Filiatrault, Harvey & Chebat, 1996; Johnston & Jones, 2004; Rutkauskas & Paulaviciene, 2005) Although the service sector has evolved into a critical element of the customer experience, there remains a scarcity of studies addressing service productivity and its improvement.
Enhancing productivity is essential for hotels to achieve their objectives and improve overall performance However, hotel productivity often lags behind other industries due to unique challenges such as high construction and fixed costs, labor-intensive operations, difficulties in mechanization, and fluctuating demand To effectively boost productivity, it is crucial that all employees across various departments collaborate, rather than placing the burden solely on one area.
Monga (2003), a Research and Programme Officer at the Asian Productivity Organization, suggests that enhancing customer focus, quality, innovation, engagement, and human resource development, along with fostering labor-management collaboration and improving working conditions, can lead organizations toward increased productivity and competitiveness.
2.4.2 Determinant for productivity improvement in hotel sector
Productivity in hotels is a complex issue, with no universally accepted methods for its analysis Some experts suggest a connection between environmental and quality management and worker productivity Ma et al (2020) found that environmental management negatively affects productivity, a conclusion supported by earlier studies (Lannelonguel et al., 2017; Frondel et al., 2018) Conversely, quality management is shown to have a positive effect on labor productivity, aligning with findings from previous research (Chapman & Khleef, 2002; Heras et al., 2011; Fonseca, 2015b).
Research indicates that implementing multiple quality management systems simultaneously can greatly enhance quality improvement and boost customer loyalty (Terziovski, 2006) In Northern Cyprus, a study by Kilic and Okumus (2005) identified key factors affecting hotel productivity, highlighting that effective staff recruitment, preparation, meeting guest needs, and service efficiency are crucial, while elements such as disasters, infrastructure, promotion, and forecasting are less significant.
Higon et al (2010) identified key elements influencing productivity in the retail sector, including competition, planning regulations, communication, knowledge transfer, human resource management, and employee skills Similarly, De Jorge and Suarez (2013) emphasized that the ability to implement best-practice technologies in hotel management significantly enhances efficiency and drives technical change Supporting this, Goel et al (2017) highlighted seven critical factors that enhance labor productivity: focus, leadership style, organizational structure, planning, adaptability, control and reward systems, and an entrepreneurial culture.
Monga (2003) proposed a model for enhancing productivity and efficiency based on four key pillars: developing a customer-oriented organization, fostering continuous improvement and technological innovation, implementing effective production management, and minimizing waste in both production processes and service delivery.
To enhance productivity, organizations must prioritize a customer-centric approach by designing, producing, and delivering goods and services that meet consumer demands in terms of timing, location, and affordability A thorough analysis of consumer needs, expectations, and behaviors—including their values, usage patterns, disposal methods, and purchase decisions—will inform a strategic corporate strategy aimed at maximizing customer value.
Continuous improvement and technological innovation are crucial for enhancing productivity Recent advancements in information technology have significantly transformed company processes and contributed to human progress, demonstrating the potential of technology It is essential for employees to embrace the identification of excess skills and new capabilities, alongside the development of retraining and redeployment strategies.
Process management focuses on achieving customer satisfaction by aligning all operations in a cohesive manner It fosters cross-functional collaboration and prioritizes meeting customer needs through innovative solutions powered by information technology By strengthening the chain of activities across various functions, process management not only enhances customer experiences but also ensures departmental unity.
To enhance service delivery, it is crucial to minimize waste, defined as anything that fails to add value for the consumer The expense associated with an operation or product does not necessarily equate to its worth; factors such as poor construction, unsuitable technology, incorrect material choices, and negligence can all contribute to inefficiencies.
19 work practices, poor management procedures, and a lack of regard for waste are all potential sources of waste.
Research Gap and Research Questions
Based on the major literature reviewed above, the summary of major research focused on the determinants of productivity improvement is presented below (See Table 2.1)
Table 2.1: Summary of empirical study about determinants for productivity improvement in service sector
No Study Sample and data Methodology Main determinants
Middle and senior managers of 4 and 5 star hotels of Cyprus
2 Kim (2010) 157 Malaysian hotels during the period from 2002 to 2004
N.A Literature review • Competition and the composition effect
• Knowledge transfer; HRM; Employee skill
At the Seoul Medical Centre,
No Study Sample and data Methodology Main determinants
Used the Amadeus database and the Spain Hotels Guide as a sample
Total factor productivity index of Malmquist (1953) by using DEA
(Eg the degree of competitiveness in the market)
• The company’s characteristics (Eg company size, type of organization, etc.)
• Deviations in business dynamics (Eg degree of technological innovation)
232 hotels with three or more stars
• Application total quality management (TQM) systems
• Adoption of the TQM principles
OECD member and nonmember countries
Human capital; labor and technology
• Business management (HRM, marketing, OB) have impact on productivity
413 employee in Indian banking sector
Regression analysis and analysis moderating effect
285 participants from who are academic staff
693 respondents from service private sectors
43 medium sized hotels in the
Descriptive and inferential statistical, OLS estimation
• Numerical, functional and zero- contract hour flexible labor management n
No Study Sample and data Methodology Main determinants
153 top-and middle-level hotel-quality managers
EFA, and linear regression analyses
• TQM improves business performance internally (higher productivity)
252 frontline employees and customers of a bank in Ho Chi Minh City, Vietnam
36,000 firms from 97 countries from four regions
• New products seem to have no effect on productivity
4266 Spanish companies in service sector
Crepon, Duguet and Mairesse (CDM) structural model
Managers and line employees from Mercure hotels in Egypt's food and beverage departments
150 papers between 1997 and 2017 and another 37 papers on the internal determinants of productivity
Literature review • Human resource management
No Study Sample and data Methodology Main determinants
572 survey questionnaires from 200 shops in Saudi Arabia
80 staffs from the selected banks multi-correlation multiple regressions analysis
• Leadership styles (participatory and charismatic)
Source: Developed by the author
The influence of various factors on productivity, particularly in the hospitality sector, has garnered significant attention in recent research Studies by Kilic and Okumus (2005) highlight that staff recruitment, training, and meeting guest expectations are crucial for enhancing productivity in hotels This finding is further supported by Kim (2010), who emphasizes that employee training and the hiring of university graduates are key determinants of technical efficiency and overall productivity in Malaysian hotels Additionally, research underscores the vital role of human resources in boosting productivity, focusing on aspects such as human capital (Joppe & Li, 2014; Brown et al., 2009), employee skills and knowledge transfer (Higon, 2010), as well as employee engagement and self-efficacy (Lee et al., 2017) A comprehensive review by Ruales Guzman et al (2019) of 150 studies from 1997 to 2019 further emphasizes these themes in the context of productivity improvement.
2017 and other studied about productivity’s determinants, finding revealed that human resources management is one of the main productivity’s determinants
Numerous studies highlight the significant role of service quality as a determinant of productivity and its enhancement Research by Benavides-Chicón (2014) indicates that the principles of Total Quality Management (TQM) positively influence hotel productivity Supporting this, Bouranta et al (2017) found that TQM characteristics serve as key factors for success and productivity improvement within the Greek hotel sector Additionally, Ruales Guzman et al (2019) established a connection between quality management and productivity, emphasizing the importance of quality management activities.
23 connected to 89 percent of the internal determinants of productivity, suggesting that
QM is a productivity determining factor
Research highlights the significant relationship between leadership and productivity, with Goel et al (2017) identifying leadership style as a key factor in boosting labor productivity Various leadership styles, including participatory and charismatic (Olanrewaju, 2020), transformational (Ojokuku et al., 2012; Al-Baradie, 2014; Singh, 2015; Abba et al., 2016), innovation (Yan, 2018), and authentic leadership (Zehir & Narcikara, 2016), have been shown to positively impact productivity in the service sector.
Research indicates a significant relationship between innovation and productivity improvement, particularly in service organizations Geum et al (2011) highlight that innovation plays a crucial role in enhancing productivity Additionally, R&D activities contribute to increased innovation, which in turn boosts productivity levels (Garcia-Pozo et al., 2018; Geum et al., 2011).
Previous studies have not thoroughly examined the impact of customer focus and process management, which are typically viewed as components of Total Quality Management (TQM) in relation to productivity (Benavides-Chicón, 2014; Ruales Guzman, 2019) While customer focus and process management are integral to TQM research on productivity improvement, waste reduction is often associated with lean services in the context of hotel productivity (Vlachos & Bogdanovic, 2013; Al-Aomar & Hussain, 2019; Hussain et al., 2019; Goshime et al., 2019).
Recent research has increasingly focused on employee satisfaction and its correlation with productivity, yet many studies primarily examine employee loyalty instead (Elegido, 2013; Frempong et al., 2018) There is a noticeable lack of research specifically addressing the relationship between employee satisfaction and productivity within the service industry Adeinat and Kassim (2019) highlight the significance of internal quality in this context.
24 employee service enhances employee satisfaction, which supports employee loyalty and productivity The findings back up Yee et al (2011) study
Prior research has extensively examined the factors influencing productivity improvement, focusing on various aspects such as human resource practices (Kilic & Okumus, 2005; Kim, 2010; Higon et al., 2010; Lee et al., 2017; Joppe & Li, 2014; Ruales Guzman et al., 2019), leadership styles (Goel et al., 2017; Olanrewaju, 2020; Ojokuku et al., 2012; Al-Baradie, 2014; Singh, 2015; Abba et al., 2016; Yan, 2018; Zehir & Narcikara, 2016), and the impact of quality on productivity (Benavides-Chicón, 2014; Bouranta et al., 2017).
Monga’s model highlights that various factors, including waste reduction, customer focus, process management, innovation, technology application, and employee and customer satisfaction, significantly impact productivity improvement, particularly in the hotel and service sectors Despite this, there is a lack of in-depth studies examining these factors within the hotel context This thesis aims to investigate the primary influences on productivity in the hotel industry and explore the relationships between the identified factors and productivity enhancement To achieve this, the research will utilize data analytics to address key questions regarding these relationships.
• How waste reduction, customer focus, process management, innovation, technology application, employee satisfaction, and customer satisfaction influence on productivity improvement in the hotel industry?
• Do the factors (waste reduction, customer focus, process management, innovation, technology application, employee satisfaction, and customer satisfaction) have a direct or indirect effect on productivity improvement in the hotel industry? n
Hypothesis development
To measure productivity and productivity improvement in the hotel sector, several studies have been conducted They were mostly focused on the following measurement scales
• Firstly, several studies examined the link between human resource practices and productivity or productivity improvement According to Kilic and Okumus
(2005), the primary productivity determinants in hotels are employee recruiting, training, and meeting guest expectations Kim's study backs up this conclusion
(2010) Some studies looked into the vital importance of human capital (Joppe
& Li, 2014; Brown et al., 2009), employee skill and knowledge transfer (Higon,
2010), or employee engagement and self-efficacy (Joppe & Li, 2014; Brown et al., 2009; Lee et al., 2017)
Service quality plays a crucial role in enhancing productivity, as highlighted in the literature Benavides-Chicón (2014) emphasizes that total quality management (TQM) principles positively influence labor productivity in hotels Additionally, research by Bouranta et al (2017) indicates that TQM components are significant predictors of increased productivity and overall success in the Greek hotel industry.
The connection between leadership style and productivity enhancement has garnered significant attention in existing literature Various leadership styles, including participatory, charismatic (Olanrewaju, 2020), transformational (Ojokuku et al., 2012; Al-Baradie, 2014; Singh, 2015; Abba et al., 2016), innovation (Yan, 2018), and authentic leadership (Zehir & Narcikara, 2016), are recognized as crucial factors influencing productivity and its improvement.
Customer happiness is a critical factor for hotels aiming to boost productivity (Minh et al., 2015) Despite its importance, there is a lack of studies examining the relationship between customer satisfaction and productivity in the hotel industry (Enaworu et al., 2018; Rew et al., 2020) Most existing research tends to concentrate on other aspects, leaving a gap in understanding this crucial link.
26 on the link between customer loyalty and productivity, or on the link between customer satisfaction and service quality (Gurau & Ranchod, 2002; Dinh et al., 2011;
Monga (2003) identifies four key pillars for enhancing productivity: customer-focused organization, technology and innovation implementation, effective process management, and waste reduction in service processes, with employee satisfaction being central to these elements While some studies, such as those by Garcia-Pozo et al (2018) and Geum et al (2011), explore the impact of innovation and technology on productivity, and others like Benavides-Chicón (2014) and Ruales Guzman (2019) examine the role of customer focus and process management within Total Quality Management (TQM), there is a noticeable gap in research on the connection between employee satisfaction and productivity Recent academic focus has shifted towards employee loyalty and its influence on productivity (Elegido, 2013; Frempong et al.).
Numerous studies have been conducted in Vietnam to explore the factors influencing manufacturing productivity (Te & Dong, 2013; Huynh & Le, 2016; Tam, 2019) However, there is a notable lack of research focusing on productivity factors within the service sector, especially in the hotel industry.
This thesis builds on Monga's (2003) research model to explore how various factors—such as waste reduction, process management, innovation, technology application, customer focus, employee satisfaction, and customer satisfaction—contribute to enhancing productivity.
Productivity improvement (PI) serves as the primary dependent variable in this research Defined as the ratio of inputs to outputs, productivity encompasses various factors such as direct raw material costs and employee numbers Outputs are measured through hotel sales, profits, market share, and overall competitiveness in the market.
27 the literature review) Then, productivity improvement will be the result of a change in the input-output ratio
On the other hand, process management, innovation, technology application, customer focus, employee satisfaction, and customer satisfaction are proposed as independent variables
• Waste reduction (WR) is defined as eliminating or reduce “anything that does not provide value to the customer” (Monga, 2003, p.50)
Process management (PM) refers to the strategic application of tools aimed at enhancing process efficiency, sustaining improvements, and consistently fulfilling consumer demands (Anh et al., 2011, p.24).
Innovation (In) refers to the introduction of a new or substantially enhanced product, service, or process, as well as novel marketing strategies or organizational methods in business practices, workplace organization, or external relations, as defined by Eurostat and OECD (2005).
• Technology applications (TA) is defined as the stage of deciding whether or not to utilize technology by an individual or an organization (Van et al., 2018)
Customer focus (CF) refers to an organization's dedication to understanding and addressing the needs, wants, and expectations of its customers—both past and present This proactive commitment is essential for long-term growth and success, as highlighted by Bartley et al (2007).
• Employee satisfaction (ES) is “the terminology used to describe whether employees are happy, contented and fulfilling their desires and needs at work” (Sageer et al., 2012, p.32)
• Customer satisfaction (CS) conceived as “the feeling of pleasure that a customer experiences after receiving services that meet or exceed the expectations of the customers” (Liat et al., 2014, p.317)
2.6.1 Waste reduction and productivity improvement
Effective waste reduction strategies can significantly minimize waste in hotel supply chains, as highlighted by Vlachos and Bogdanovic (2013) Hotel waste encompasses both visible elements, such as water and oil, and intangible factors like errors and delays Implementing these strategies can lead to a more sustainable and efficient operation in the hospitality industry.
Despite its strong connection to improved lean implementation and productivity in the hotel supply chain, waste reduction has received limited attention Research indicates that lean concepts and practices, particularly waste reduction, are still in the early stages within the hotel industry, with minimal studies conducted to evaluate their implementation.
To enhance productivity, it is essential for employees to recognize the benefits of waste elimination, such as minimizing wasted time, thereby fostering a positive association with lean practices (Leite, Bateman & Radnor, 2020) Effective resource utilization leads to the removal of all forms of waste, including non-value-adding activities, maximizing resource efficiency, ensuring timely product delivery, and improving product quality through enhanced creativity and skill development among employees (Goshime et al., 2019) Consequently, the first two hypotheses of this thesis are proposed.
H1: Employee Satisfaction is directly related to Waste Reduction
H2: Productivity Improvement is indirectly related to Waste Reduction
2.6.2 Process management and productivity improvement
Process management significantly influences employee satisfaction, as highlighted by Eskildsen and Dahlgaard (2000) Alvarez-Garcia et al (2015) further affirmed that process management and continuous improvement are key antecedents of employee satisfaction Additionally, Amin et al (2017) found that seven soft Total Quality Management (TQM) approaches, including process management, notably enhance both staff satisfaction and hotel performance.
Research by Ruales Guzman et al (2019) identifies process management as a crucial element of quality management (QM) activities that significantly enhances productivity Furthermore, Alinejad and Anvari (2018) demonstrate that effective process management serves as a valuable tool for boosting productivity and fostering innovation, contingent upon the varying levels of process design, control, and development.
29 tailored to suit the collaboration and competition force From the points of view, the following hypothesis is generated:
H3: Employee Satisfaction is directly related to Process management
H4: Productivity Improvement is indirectly related to Process management
Final proposed research model
Building upon hypotheses development and concept of each variable, the thesis come up with the below conceptual framework:
RESEARCH METHODOLOGY
Sampling and data collection
Research ideally targets the entire population, but practical constraints often necessitate the use of samples In this study, the focus will be on hotels operating in Danang City, Vietnam, which serve as the selected sample for analysis.
This research investigates the factors influencing productivity improvement in the hotel industry, focusing on both direct and indirect effects, with customer and employee satisfaction serving as mediators Utilizing a convenience sampling approach, the study is conducted in Danang, a major travel destination in Vietnam known for its high hotel density and substantial population, making it an ideal location for this investigation.
The questionnaire, originally developed in English from previous research, was translated into Vietnamese and meticulously reviewed for quality by a Vietnamese supervisor This questionnaire is specifically tailored for Vietnamese hotel managers or representatives, with detailed information available in Appendix A.
The "Productivity Improvement" measurement scale consists of 7 items, adapted from the foundational research of Sigala (2004) and De Jorge and Suarez (2013) Additionally, the "Customer Focus" measurement scale includes 6 items, derived from the studies conducted by Alem Mohammad et al (2013) and Bouranta et al.
The measurement scale for Process Management consists of 10 items adapted from Litos et al (2011) For Innovation, a 7-item scale was selected and modified based on the studies of Nieves et al (2014) and the Oslo Manual (Eurostat & OECD, 2005) Additionally, the Waste Reduction measurement scale includes 6 items developed from the research of Vlachos.
The measurement scale for Technology application consists of 7 items, adapted from the studies of Oltean et al (2014) and Melián-Alzola et al (2020) Employee satisfaction is measured using a scale of 10 items, based on the research conducted by Trang (2013) Additionally, the Customer satisfaction measurement scale includes 4 items, adapted from the work of Pereira-Moliner et al.
Table 3.1 below will present the content of each measuring item used in the thesis
The thesis utilizes an extensive amount of primary information gathered through a pencil-and-paper questionnaire, which is essential for data collection in scientific studies To investigate the factors contributing to productivity improvement in the hotel industry, the author developed a comprehensive questionnaire consisting of 57 items, divided into two sections.
• The first part is used to address the demographic information of attendants
The article discusses the measurement of dependent variables such as Employee Satisfaction, Customer Satisfaction, Waste Reduction, Customer Focus, Process Management, Technology Applications, and Innovation, alongside the independent variable of Productivity Improvement.
Responses to the survey items, excluding demographic questions, utilized a 5-point Likert scale, where 1 indicated total disagreement, 2 represented disagreement, 3 signified a neutral stance, 4 indicated agreement, and 5 denoted total agreement.
Table 3.1: Measuring items for survey
There is a trend in increasing hotel productivity over the financial years
The hotel's average revenue per employee has grown significantly
The hotel's average profit per employee has grown significantly
The hotel's business market share has been significantly expanded
The hotel's competitiveness is significantly enhanced PI5 The rate of wasting investment capital per employee in business is significantly reduced
The efficiency of using input materials has increased significantly
Employees at the hotel express satisfaction with various aspects of their job, including the nature of their work, salary, and salary increase policy Additionally, they appreciate the bonus policy and welfare regimes offered by the hotel Furthermore, there is a positive sentiment regarding promotion opportunities within the organization.
Employee satisfied with the supervision of my supervisors within hotel
Employee satisfied with their relationships with fellow workers within hotel
Employee satisfaction increases year by year ES9 The rate of employees changing jobs, quitting their jobs does not affect business activities
Customers satisfaction with hotel’s products and services CS1 The level of customer complaints has decreased significantly in recent years
The level of customers with positive feedback has increased significantly in recent years
The percentage of customers retention has increased in recent years
Hotel actively reviews functions, tasks, job descriptions, and assigns jobs to access lean organizational and human resources
Hotel actively optimizes management and business processes to reduce waste in all business processes
Hotel actively implements strict service quality controls to eliminate waste caused by poor service quality
Hotel actively exercises control over input purchases & supplies to eliminate waste in inventory
The hotel actively works to save and prevent wastefulness of energy, fuel and raw materials
The hotel actively practices reduce waste in business expansion and investment
Satisfying our customers, and meeting their expectations, is the most important thing we do
Hotel implemented several measures to improve the process, renovate equipment, employee training,… to improve customer satisfaction
Hotels actively do market research and analyze customer data to better understand customer needs and expectations
Processes and business standards, the hotel employee job KPIs are built on the basis of market research and customer information
Feedbacks and complaints from customers about the service are always handled quickly, promptly and accurately to satisfy customers
Our employee training programs are designed to develop the skills required for acquiring and deepening customer relationships
Hotel staffs are trained in skills to enhance the customer experience
Hotels build a unique process for customer experience PM2 Hotel offers flexible booking policies for customers PM3 Hotel answers questions and gives full information when contacting customers
Interaction and communication activities between employees and customers are done professionally, accurately, friendly, and satisfy customers
Internal interaction activities between employees in front of customers professionally and effectively
Internal interaction activities between employees in the absence of professional and effective customers
Hotel focuses on after sale services PM8
Hotel’s facilities to meet the needs of customers PM9 Hotel offers personalized products and services for each customer
Hotels use information systems dedicated to bookings (TripADvisor, Agoda, Hotel.com, Booking, etc)
Hotels have a developed application type Customer Relationship Management
The hotel's website supports multiple functions (booking, payment, information )in providing services to customers
Hotels are always actively looking for technologies to apply in business activities to better serve customers
Extension of the hotel's products and services (Wi-Fi, Lan Network video game consoles and/or electronic books in the rooms…)
Hotels store and analyze customer information to learn customer behavior, forecast customer needs
The hotel is oriented towards the 4.0 hotel model (automation applications, Internet of Things, smart hotels)
Hotels have introduced many new products/services onto the market
Hotels improves the efficiency and speed of product / service delivery for urgent needs
Hotels enhance their offerings by diversifying the range of products and services available, improving their quality, and increasing flexibility in delivery They also prioritize speed in service delivery and focus on developing environmentally friendly options to meet the growing demand for sustainable practices.
Analyzing data plan
The data will be entered first, then screened to exclude any invalid entries, which will be rejected The data will then be encoded as seen in table 3.1
The internal consistency approach employs Cronbach's Alpha to evaluate the reliability of scales Prior to performing factor analysis, it is essential to utilize the Cronbach's Alpha coefficient to eliminate unsuitable variables, as these irrelevant variables can lead to misleading factors (Nguyen & Nguyen, 2009).
Cronbach's alpha is a key measure of scale reliability, with values above 0.9 indicating excellent reliability and values below 0.5 suggesting weakness (George & Mallery, 2010) To effectively measure Cronbach's alpha, a scale should consist of at least three items Additionally, item-total correlation plays a crucial role in assessing the relationship between individual items and the overall scale, with correlations below 0.3 deemed unacceptable and those above 0.3 considered satisfactory (Nunnally & Bernstein, 1994) Evaluating these criteria is essential for ensuring the reliability of measurement scales.
• Corrected Item-Total Correlation: The observed variables with Corrected item- total correlation small (< 0.3) are considered to be garbage variables and will be n
40 removed and the scale will be accepted when Cronbach’s Alpha reliability factor is met
• Cronbach's Alpha if Item Deleted: When a specific item is removed from the scale, the Cronbach's alpha reliability coefficient for internal consistency is displayed
Factor Analysis (FA) is a valuable method for evaluating two essential scale values: discriminant value and convergence value As an interdependence technique, FA operates without independent variables, relying instead on the correlations among variables For effective exploratory factor analysis, certain conditions must be met.
• Percentage of variance is greater than or equal to 50%
Pearson correlation analysis is essential for assessing the linear relationship between dependent and independent variables, confirming the appropriateness of linear regression analysis The Pearson (r) correlation coefficient ranges from -1 to +1, with an absolute value of 1 indicating a strong linear correlation between the two variables Conversely, an r value of 0 signifies no linear relationship exists between them (Hoang & Chu, 2005).
Regression analysis is a statistical modeling technique used to explore the relationship between one or more independent variables (X1, X2, X3, , Xk) and a dependent variable (Y) When a linear relationship is identified between these variables, linear regression can be employed to model this causal connection Key requirements must be met for the regression model to be valid.
• Sig value is less than 0.05 and is the condition for the variables to be included in the research model
• No autocorrelation (Consider Durbin Watson)
• R-squared makes sense: R-square indicates the percent variable of the dependent variable explained by the independent variables affecting it
Path analysis is employed to evaluate the study's framework and assumptions, while regression analysis estimates the relationships between independent and dependent variables The standardized regression coefficients indicate the directional relationships between these variables, with their associations deconstructed into total direct and indirect impacts To streamline the model, routes with coefficients not statistically significant at the 0.15 level or lower should be excluded prior to decomposition (Flynn et al., 1995) Additionally, assessing the goodness-of-fit is crucial for ensuring the model's effectiveness in analysis The path analysis will utilize SPSS/AMOS 20 (free trial version), adhering to specific goodness-of-fit criteria.
• Root Mean Square Error of Approximation (RMSEA, 90% confidence interval)