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Exploring the Relationship Between Hotel Classification System and Service Quality: A Case Study of the Indian Hotel Industry
- First Online: 05 January 2022
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- Tahir Sufi 6
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This case study explains the concept of the hotel classification system in the backdrop of its influence on hotel service quality. In addition to understanding the concept of hotel classification, the students shall also be able to understand the issues and controversies surrounding this system in India. The hotel classification systems act as a signalling mechanism to inform guests about what to expect from the hotels at various price points. The hotel classification systems around the world claim to enhance hotel service standards and better customer satisfaction. However, such systems are prone to criticisms for focussing on hotel infrastructure and failing to ensure hotel service standards.
The industry experts and other stakeholders are sceptical about the classification process. Using this criticism as a backdrop, this case study investigates the relationship between the hotel classification system and service quality in India. The questionnaire method is used in this case study to explore hotel managers and customers perceptions of the influence of hotel classification on hotel service quality. The results of this case study indicate that the hotel classification system does have a positive influence on hotel service quality.
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Suggested Readings
Behnke, C., Torres, E., & Adler, H. (2014). Stars, diamonds, and other shiny things: The use of expert and consumer feedback in the hotel industry. Journal of Hospitality and Tourism Management, 21 , 34–43.
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Department of Business Administration, University of Piraeus, Piraeus, Greece
Marianna Sigala
Strategy and Operations Discipline, Kaplan Business School, Brisbane, QLD, Australia
Anastasia Yeark
Blue Mountains International Hotel Management School, Torrens University, Sydney, NSW, Australia
Rajka Presbury
Faculty of Higher Education, William Angliss Institute, Melbourne, VIC, Australia
Marcela Fang
Wellington School of Business and Government, Victoria University of Wellington, Wellington, New Zealand
Karen A. Smith
Teaching Note
Case summary.
This case study aims at exploring the hotel manager’s perceptions about the hotel classification system in the backdrop of criticism about the system. While the classification system of India emphasizes on providing contemporary standards of facilities and services available in the hotels-however, industry experts have doubts about the system. The hotel industry experts in India believe that standards prescribed by the hotel classification system are too low in comparison to what the hotel brands offer. The lack of research studies in this area further complicates the matter. There are less than one per cent classified hotels in India- that confirms such doubts and apprehensions about the system. This case study, therefore, attempts to explore all these questions through quantitative techniques.
Teaching and Learning Objectives
Hotel rating systems are neglected in the academic curriculum around the world despite their importance in booking related decision by the customers. The hospitality schools worldwide have ignored the rating process due to which the graduates lack the understanding of the concept when they enter the hotel Industry. This case study aims at the following objectives:
Understand what the hotel classification system is.
Understand the issues and challenges of the hotel classification system .
Explore the significance of the system.
Target Audience
This case study explains the hotel rating system concept in a simple manner that can be understood by graduate-level students easily. However, at the same time, this study offers valuable insight into the system for academicians, managers, and policymakers equally. Hotel rating policy documents can be too abstract and difficult to grasp. This case study offers the theoretical concepts rooted in service quality management to explore the system.
Teaching Approach and Strategy
It is recommended that the students are introduced to the following concepts before the actual discussion on this case study:
A brief history of the evolution of the hotel classification process.
Types of the classification processes.
Advantages and disadvantages of the system.
These concepts can be introduced through the use of a PowerPoint presentation by the instructor. After introducing the concept of the hotel classification, the instructor can distribute the copies of this case study to the students and allow one and half hour study time. The students can be segregated in the groups of 4–6 students and asked to answer the discuss the following points:
Is the criticism of the hotel rating system justified?
How can the hotel rating systems be upgraded to meet customer expectations?
What is the impact of the internet on the traditional hotel classification ratings?
Should the classification system be made digital now?
How can hotels be evaluated to ensure that only hotels with top service quality are awarded higher ratings?
What are the various techniques by which hotel service quality is evaluated?
Which techniques are effective for evaluating hotel service quality in your opinion? Why do you think so?
Analysis of Data
What insight does Tables 11.5 and 11.6 provide? Why do you think customers rate the areas of hotel classification higher as compared to the managers?
Is this the right approach to evaluate the classification system?
What could better methods have been applied?
Can you identify different research areas after reading this case?
Is the use of the research techniques justified?
Example Responses
Answer 1. Table 11.5 has indicated that the customers rate the areas of hotel classification more favourable as compared to managers. Table 11.6 show that managers of unclassified hotels (without star ratings) have a more favourable opinion of the classification system as compared to the managers of unclassified hotels.
The managers of the classified hotels seem to have doubts and apprehension about star ratings. The managers are expected to follow the hotel brand standards and SOS’s daily, which they believe are more stringent and effective in ensuring service standards. In comparison, guests high expectations from all the areas of hotel classification offers an exciting insight in contrast to a review of the literature review. There is a clear indication that there is an image problem with the system- which perhaps is due to a lack of innovation in hotel evaluation.
Suggested Group Activity
Compare the booking procedure of hotels through any hotel website and OTA’s (MakeMyTrip, Hotels.com etc.). Students are suggested to note the differences in making hotel booking through different sources and present a report on the same.
Note ten positive reviews of a five-star deluxe hotel and ten negative reviews. Prepare a report on what the guest like most about hotels and what guests dislike about hotels.
Download any leading hotel classification document from the internet. List ten strengths and ten weakness in terms of its contribution to enhancing hotel service quality.
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Sufi, T. (2022). Exploring the Relationship Between Hotel Classification System and Service Quality: A Case Study of the Indian Hotel Industry. In: Sigala, M., Yeark, A., Presbury, R., Fang, M., Smith, K.A. (eds) Case Based Research in Tourism, Travel, Hospitality and Events. Springer, Singapore. https://doi.org/10.1007/978-981-16-4671-3_11
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Model of Quality Management Systems adoption in the hotel industry: A case study of hotels in Zimbabwe
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Article Category : Research Article
Published online : jun 29, 2022, page range: 230 - 239, received : jun 14, 2021, accepted : dec 02, 2021, doi: https://doi.org/10.2478/ejthr-2021-0021, keywords quality management systems , hotels , internal factors , external factors , model, © 2022 vitalis basera et al., published by sciendo, this work is licensed under the creative commons attribution 4.0 international license..
The construction of a model fit for implementing quality management systems (QMS) is presented. The article features the main internal and external factors that were found in a research including nine case study hotels in Zimbabwe. There is late adoption of QMSs in the hotel industry with few organisations having adopted certified QMSs ( Basera, Mwenje, & Ruturi, 2020 ). Hotels were not spared from tough competition resultant from globalisation and a volatile operating environment in the country. Some hotels closed while others had low-capacity utilisation due to low competitiveness ( Zimbabwe Tourism Authority, 2016 ). Others persisted and remained competitively operational; researchers believed that adoption of QMS is among many other reasons that enabled their survival ( Zengeni, Mapingure, Zengeni, & Marimbe, 2014 ). Since independence in 1980 Zimbabwe went through different phases of economic challenges, putting into effect different economic turnaround strategies with little to no positive results. The ushering in of the Second Republic in 2017 introduced the Transitional Economic Stabilisation Programme (TESP) and National Development Strategy 1 (NDS1) as strategies towards achieving Vision 2030: ‘Towards a Prosperous and Empowered Upper Middle-Income Society’ ( Government of Zimbabwe, 2021 ). The study-specific objective was to offer an appropriate model for successfully adopting QMSs in the hotel industry in Zimbabwe for the realisation of Vision 2030, since tourism is one of the key pillars for achieving sustainable economic development. The Grounded Theory method as apprised by the Eisenhardt Model (1989) was used in this study. Internal and external factors impacting hotels in their quest to successfully adopt QMSs are presented in this article and were used in the construction of the BASERA-MWENJE model of QMS adoption. This model is suggested for use by hotels and other firms that seek to effectively adopt QMSs.
Tourism and the hospitality industry have undergone enormous growth globally, until the emergence of the COVID-19 pandemic. This growth affords the industry huge opportunities and equally huge challenges; change in demand, new tourist profiles, aggressive competition, use of new technology and the emergence of traveller communities ( United Nations World Tourism Organisation, 2018 ). The new challenges require the hotels to improve their in-house efficiency and maintain a sustainable advantage ( Muzapu & Sibanda, 2016 ). One of the most widespread ways of dealing with challenges of this nature involves the institution of certified quality management systems. Such systems have helped thousands of companies to be competitive the world over using quality management practices that are audited by independent third parties ( Wang, Chen, & Chen, 2012 ). According to Islam, Habes, Karim, & Syed-Agil (2016, p.635) , obtaining quality certification is a ‘market signal’ that enables ‘an organisation to communicate about its unobserved quality attributes and consequently a certified organisation may be able to gain an advantage against its non-certified competitors’.
Implementing a quality management system can bring benefits to hotel organisations, as it can improve efficiency and corporate image. Quality management systems can be used as management tools that change the operations and internal processes of hotels. Motives for adoption of QMS by organisations are improving internal control, reducing cost, enhancing service quality to reduce failures and complaints, improving efficiency, increasing labour productivity and motivating employees, or providing the first step toward more developed quality models, such as Total Quality Management (TQM) ( Ahmed, Coffey, & Xia, 2017 ). Certification improves hotel quality image and quality differentiation; it can be implemented in response to pressure from customers or competitors. QMS have been researched especially in the manufacturing industry by many authors. Beginning in the 1950s ( Deming, 1986 ; Juran, 2016 ; Crosby, 1979 ; Ishikawa, 1979 ; Oakland, 2011 ; Shingo, 1985 ) and later on in the 1980s, research focused on quality in the service industry ( Zeithaml, Berry, & Parasuraman, 1990 ). QMS is a set of coordinated activities to lead and control an organisation in terms of quality ( ISO, 2015 ).
Zimbabwe is the second-largest tourist destination in Southern Africa. The total contribution of tourism to Gross Domestic Product (GDP) in 2016 was $USD 0.5 billion which contributed 3.5% of the total GDP ( World Tourism Council, 2018 ). The tourism sector in Zimbabwe contributed about 5.1% of jobs in the country, with around 159,500 employed in the industry for 2016 alone ( Zimbabwe Tourism Authority, 2016 ). In 2016, the total contribution of travel and tourism to employment, including jobs indirectly supported by visitor exports, generated USD 0.2 billion, which is 7.3% of total exports (World Tourism Council, 2018). Whilst the industry was second-best in Southern Africa, its contribution was significantly very little as compared to USD 8.7 billion to the GDP of South Africa ( World Tourism Council, 2018 ). A study by Zengeni, Mapingure, Zengeni, and Marimbe (2014) showed that local hotels are increasingly facing quality problems and need to adopt quality management systems to improve their competitive advantage by reducing costs of services, improving service delivery and improving quality of products. Hotels have failed to adopt quality management systems due to a variety of reasons: lack of finance, lack of support from the owners, resisting change, cultural and religious beliefs and high cost of finance (Basera, Mwenje, & Ruturi, 2019). Apparently, hotels in Zimbabwe seem to be struggling with adoption of QMS. Recent efforts by the Hospitality Association of Zimbabwe (HAZ), Standards Association of Zimbabwe (SAZ) and Zimbabwe Tourism Authority (ZTA) to engage hotels to standardise their products and services have not yielded much anticipated results, as most of them fail to acquire credit or working capital to standardise their products ( Zhou, 2018 ). Research shows that failure to standardise products and services results in variation of product quality, poor service and wastage of resources and ultimately results in reducing customer base, which affects revenue of hotels.
The philosophy of quality management, factors affecting QMS, is principally credited to a number of quality and strategic management gurus such as Deming (1986 , 1950, 1993), Juran (1988, 2012), Oakland (2003, 2014, 2011 , 2006), Shingo (1989) and others. As competition intensifies, adopting QMS is a desirable goal, even necessary for business survival. ISO 9000 posits that companies that adopt QMS continuously outperform others, meeting global business excellence standards, knowing closely their suppliers and customers, understanding their competitors’ performance capabilities, and understanding their employees. Successful adoption of QMS in organisations has led to sustainable competitiveness of businesses. Organisations that are quality certified have access to markets in the global village thereby increasing competition. Globalisation is the key driver of QMS adoption. Globalisation is the process of integration and interaction among people, companies and governments worldwide through advanced transportation, communication and trade ( PIIE, 2021 ).
A quality management system is a set of coordinated activities to lead and control an organisation in terms of quality ( ISO, 2015 ). Pereira-Moliner et al. (2012) and Fonseca (2015) reported that a number of authors defined QMS as that part of a management system which focused on leading and controlling an organisation in relation to quality. There are macro quality management systems applicable in any organisation and there are micro quality management systems which are industry specific. Macro QMS include Total Quality Management, ISO 9001, continuous improvement, Six Sigma, lean production, benchmarking, and Business Excellence. Micro QMS are industry specific. The micro QMS in the hotel industry include Hazardous Analysis Critical Control Point (HACCP), ISO 22000, Food Safety Management (FSM), Assured Safe Catering (ASC) and ISO 22483:2020 Tourism and related services—Hotels Service requirements.
Nine hotels that are 1- to 3-star rated were studied using Eisenhardt's Model of building theory from case studies. Eisenhardt's (1989) approach to building models was used to explain and understand the integrally dynamic nature of numerous factors affecting QMS adoption. The research implemented a positivist interpretation of research, relying greatly on previous literature and pragmatic data as well as on the insights of the researchers to construct a stronger model. The steps of building a model from case study research (getting started, selecting cases, crafting instruments and protocols, entering the field, analysing data, shaping hypothesis, enfolding literature, reaching closure) were followed as given by Eisenhardt (1989) . Model construction from case study research is likely to have important strengths—novelty, testability and empirical validity—which arise from the intimate linkage with empirical evidence. The case-hotels are identified in this article by the key code H1, H2, H3, H4, H5, H6, H7, H8, H9. It began with the view that adoption of QMS had been late among low-rated hotels, and those that intended to adopt QMS produced unfavorable results. All the nine case hotels have attempted to implement or have implemented QMS with different levels of success. Data was collected using focus group discussions and interviews to answer the research questions. Focus group interviews were done with hotel employees; in-depth interviews were done with hotel managers and key stakeholders. The case hotels were purposively selected, and interviews and focus groups were done until saturation was reached on themes of study interest.
There were many QMSs that have been established over the years but the case hotels had adopted those shown in Table 2 .
All the hotels adopted benchmarking; no hotel had adopted ISO22483: 2020 or Six Sigma quality management systems. Six Sigma is more applicable to manufacturing industries than service industries, and its adoption in service industries is low ( Pai-Bhale, Srividhya, Mariappan, Sony, & Belokar, 2017 ). ISO22483:2020 are quality management standards that are specific to hotels and had been launched recently (2020), which might be the reason why no hotel had adopted them. Related key factors were revealed that are contributing to late adoption of QMS in the hotel industry.
Eighteen factors were established across the nine case hotels. Cheah, Wong and Deng's (2012) model was used to rank the factors, displaying the connections that exist among the factors. Level I factors are internal, those that are highly controllable by the hotel; they are dependent on and affected by external factors. Level I is at the core of any QMS adoption strategy and at the top of priority. Level II factors are those that are affected by Level III factors and also influence Level I. Level III factors affect all the others and are independent to some extent. Classified associations of the key factors in the study are shown in Figure 1 . The factors arose from case analysis and their brief description is given in Table 2 . The factors were the imperative pointers from case evidence of the vital considerations by hotels during adoption of QMSs. Relationships between the factors and their impact was established, and used in constructing model for adopting QMS.
Classified classification of factors
![quality hotels ltd case study quality hotels ltd case study](https://sciendo-parsed.s3.eu-central-1.amazonaws.com/6471bd88215d2f6c89daf54f/j_ejthr-2021-0021_fig_001.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20240902T204003Z&X-Amz-SignedHeaders=host&X-Amz-Expires=18000&X-Amz-Credential=AKIA6AP2G7AKHMOEQWMW%2F20240902%2Feu-central-1%2Fs3%2Faws4_request&X-Amz-Signature=7d429a2fdc9148afca70f5b58d0eaf5c39f5f17fb8f07b6e2a6c52b4fe35a85d)
Changing political and economic environments dictate that management establish a favorable environment that will aid in enhancing the success in the adoption of QMSs. Management/Leadership need to put strategies in place that mitigate the impact of Level III factors (external factors).
A model that enables hotels to successfully adopt quality management systems was developed. All 9 case hotels provided useful insights, but of importance were successful QMS adoptions from H1, H2, H7 and failures of QMS adoption from H4, H8 and H9, as presented in Table 1 . Case evidence from H3, H5 and H7 were not disregarded, as they were merged in the subsequent cross-case analysis. This evidence, linked with gaps located in literature, developed the foundation of the BASERA-MWENJE model for adopting QMS, shown in Figure 2 . The model is named using Ubuntu values, using the surnames of the researchers. Coincidentally, Basera means ‘something given as extra’ and Mwenje means ‘light’, thus BASERA-MWENJE means extra light needed in successful adoption of QMSs.
Summary of quality management systems
Total Quality Management (TQM) | TQM is used by management to enhance efficiency, flexibility and competitiveness of a business as a whole. To attain implementation of TQM, management must be involved in the improvement of quality, organisation culture must change, quality strategy must be developed, staff must be trained, and quality costs determined. Introduced by Feigenbaum through his concepts of Total Quality Control ( ). | 1952 |
ISO 9001:2015 | This standard is based on a number of quality management principles including a strong customer focus, the motivation and engagement of top management, a process approach and continual improvement. It is founded on the same quality principles as ISO 9001:2008 but adds new requirements of risk-based approaches and knowledge management. Introduced by International Standards Organisation ( ). | 1987 |
ISO 22483: 2020 | This standard establishes quality requirements and recommendations for hotels regarding staff, service, events, entertainment activities, safety and security, maintenance, cleanliness, supply management and guest satisfaction ( ). | 2020 |
Lean production | Its main principle is to focus on time and effort, to identify and refine steps in an operation that the customer deems valuable, and to eliminate wasteful or unnecessary steps in a process. Originated in the Toyota Motor corporation ( ). | 1991 |
Six Sigma | This is a controlled, data-driven approach and methodology for eliminating defects in any process from manufacturing to transactions, and from product to service. Was first introduced at Motorola as a method to measure and improve high-volume production processes ( ). | 1980's |
Benchmarking | Organisations compare themselves with the best and constantly review their processes, practices and methods to guarantee the strength of their competitive position relative to their competitors. Xerox executives started talking of benchmarking as a quality improvement tool ( ). | 1980 |
Continuous Quality Improvement (CQI) | This is a philosophy that focuses on improving processes to enable companies to give customers what they want the first time, every time, subject to improvement. It came into existence initially in manufacturing as an alternate improved approach to TQM in effort to improve products, services or processes ( ). | 1970s’ |
Business Excellence Models | They provide guidelines for effective quality management and may be used as self-assessment models. TQM is the basis of BE because the fundamental philosophies are the same: participation of top management, stakeholder involvement, and holistic approach. The most distinguished BE models applied the world over are the Deming Prize, Malcolm Baldrige National Quality Award (MBNQA), European Foundation for Quality Management (EFQM), Australian Quality Award (AQA) and Canadian Quality Award ( ). | 1988 |
Business Excellence Models | They provide guidelines for effective quality management and may be used as self-assessment models. TQM is the basis of BE because the fundamental philosophies are the same: participation of top management, stakeholder involvement, and holistic approach. The most distinguished BE models applied the world over are the Deming Prize, Malcolm Baldrige National Quality Award (MBNQA), European Foundation for Quality Management (EFQM), Australian Quality Award (AQA) and Canadian Quality Award ( ). | 1988 |
Statistical processes control (SPC) | This uses statistical means to manage a process to confirm that it functions at its full potential to produce a product that meets requirements. Control charts, graphs, scatter diagrams, cause-and-effect diagram, pareto chart, histogram, and check sheets are seven tools in SPC. It was first laid out at Bell Laboratories by Walter A. Shewhart ( ). | 1920 |
Hazard analysis critical control point (HACCP) | It is a science-based quality management system with the focal goal to stop contamination of food. HACCP is used to identify and evaluate chemical, microbiological and physical hazards. It was first developed by the U.S. National Aeronautics and Space Administration (NASA) ( ). | 1960 |
Assured safe catering (ASC) | ASC is a system developed for and with caterers and food producers to control food safety problems based on principles of hazard analysis and critical control points ( ). | 1980s |
Quality management systems adopted
Total Quality Management (TQM) | |||||||||
Lean production | |||||||||
Six Sigma | |||||||||
Benchmarking | |||||||||
Continuous Quality Improvement (CQI) | |||||||||
Business Excellence Models | |||||||||
Statistical processes control (SPC) | |||||||||
Hazard analysis critical control point (HACCP) | |||||||||
Assured safe catering (ASC) |
BASERA-MWENJE model of QMS adoption
![quality hotels ltd case study quality hotels ltd case study](https://sciendo-parsed.s3.eu-central-1.amazonaws.com/6471bd88215d2f6c89daf54f/j_ejthr-2021-0021_fig_002.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20240902T204003Z&X-Amz-SignedHeaders=host&X-Amz-Expires=18000&X-Amz-Credential=AKIA6AP2G7AKHMOEQWMW%2F20240902%2Feu-central-1%2Fs3%2Faws4_request&X-Amz-Signature=f508ff852e1f8e571b05fd95a91138e5e6feca9bfadafc3899f5117b7db3e1ad)
The house metaphor was used in the model. A strong house withstands adverse environmental conditions and continues to serve, while a weak one gives in to the same environmental conditions. In much the same way hotels that desire to adopt QMSs that would be successful and sustainable need to consider the house metaphor. The internal factors are the foundations, the external factors are the walls, and the roof is the ultimate outcome of sustainable competitive hotel operations. An eighteen-step model to constructing the BASERAMWENJE model of QMS adoption was developed from the identified factors affecting QMS in the hotel industry. The BASERA-MWENJE model key objective is to alleviate and overcome the key factors that were found from the research to delay adoption of QMS as well as ensuring sustainability of the adopted QMSs.
The model consists of eighteen steps: seven internal steps, ten external steps and one step which integrates internal steps and external steps. The eighteen (18) BASERA-MWENJE steps of implementing QMS are shown in Figure 3 and each is described subsequently. Each step leads to the next, making the order of the steps a vital feature of BASERA-MWENJE Steps.
BASERA-MWENJE steps in adoption of QMSs
![quality hotels ltd case study quality hotels ltd case study](https://sciendo-parsed.s3.eu-central-1.amazonaws.com/6471bd88215d2f6c89daf54f/j_ejthr-2021-0021_fig_003.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20240902T204003Z&X-Amz-SignedHeaders=host&X-Amz-Expires=18000&X-Amz-Credential=AKIA6AP2G7AKHMOEQWMW%2F20240902%2Feu-central-1%2Fs3%2Faws4_request&X-Amz-Signature=f45b9ed35dd3ef38605bd09f7ceaf7482a302f7ee2414fe108a885e7213dd186)
Brief explanation of internal factors
Employee involvement | Employee involvement deals with how the firm empowers and enables its employees to develop their potential and how the employees are inspired to attain the firm's objectives. Employees’ involvement in decision making is one of the sustainable ways of adopting QMS in the hotels. Employees know and understand customer needs, and they are key parts of QMS. Employees are capable of repairing dented quality of the service. |
Effective management/leadership | Management or leadership of hotels should be responsible and accountable for forming and communicating a quality vision and QMS adoption strategies for organisation continuous improvement. Effective leadership or management style should be adopted that involves employees in decision making so as to achieve positive business results. |
Trend technology | It is essential for the hotels to implement the latest technology in their operations; good communication inside and outside their organization and safe storage of information reduces operating costs and affords adoption of QMS. |
Strategic Management | Management of hotels must come up with a vision that embraces quality and strategies for QMS adoption: allocation of resources, product offerings, and systems to manage ambiguities prevailing in the business environment should be aspects of this vision. |
Qualified and skilled employees | Hotels should hire qualified and skilled employees to add value to their quality strategies. |
Quality function/committee | The management of hotels is supposed to set up a specialised quality management department responsible for quality issues, or at least a quality committee if resources do not permit a department. |
Product development | Hotels need to involve employees and customers when coming up with new products, service delivery systems and any new way of doing things. This overarches both internal and external factors. |
Financial resources | The hotels need to set aside budget for implementation of QMS, to train staff, hire or pay quality consultants, procure of necessary equipment, and other associated costs. |
The BASERA-MWENJE model of QMS adoption reflects how the established main factors are managed in adopting QMSs with exclusive reference to the hotel industry in the Zimbabwean setting. Step 1 to Step 7 reflects what is supposed to be followed within the organisation. Step 8 involves both internal stakeholders and external stakeholders. Step 9 to Step 18 reflects what is supposed to be followed in the external environment involving industry multistakeholders. In order to comprehend the sustainable adoption of any selected QMSs, organisations should follow the eighteen BASERA-MWENJE steps.
The BASERA-MWENJE model of QMS adoption was compared with other models to identify similarities and differences.
Brief explanation of external factors
Government policies | Taxes and license fees should be designed in a way that encourages adoption of QMS in the hotel industry. Access to cheap funds and rebates encourages hotels to improve quality of their products. |
Business excellence models/best practices | There is need for Business Excellence Models, since they provide guidelines for effective quality management and may be used as self-assessment models. |
Relationship networks | Hotels need to affiliate or relate to key industry stakeholders, to cooperate and exchange resources, ideas, knowledge and information in the industry for improved adoption of QMS. |
Sustainable competition and coopetition | Hotels need to consider sustainable competition and coopetition as fundamental pillars of QMS adoption. |
Corruption and crime free | Hotels should not tolerate corruption in the licensing process and remittance of statutory fees if they are to embrace genuine quality in their organisations. |
Foreign currency | Availability of foreign currency is very critical for quality improvement in the hospitality industry. |
Supporting infrastructure | There is need to make sure that there is adequate and reliable supply of water, electricity and internet, as they are basics of quality in the hotels. |
Benchmarking | Hotels need to learn from each other, copying quality strategies from those performing well, generating new ideas on how to improve. |
Stable economy | Hotels can easily adopt QMS when operating in a normal economy with consistent economic policies for them to plan and invest towards it. Management of hotels should come up with mechanisms for dealing with economic shocks, so that the quality strategies are not disturbed. |
Customers | It is important to listen to customers’ voices to improve quality in the hotels. |
It shares certain similarities with the WILGOR Framework of Manufacturing Excellence ( Goriwondo & Madzivire, 2015 ) and the Madzivire Collaborative Transformation (MaCoTra) Model ( Madzivire, 2011b ). Some differences do exist. The WILGOR Framework of Manufacturing Excellence concerns organisations that want to adopt World Class Manufacturing (WCM) status, in the way that the BASERA-MWENJE model speaks to organisations that want to adopt QMSs. The MaCoTra Model speaks to organisations that want to transform. Organisations moving from their current status to adopt QMS require transformation.
Some similarities were established in contrast with the SHINGO Model ( The Shingo Institute, 2021 ). The SHINGO Model was crafted to direct organisations desiring to transform organisational culture to attain quality results. The SHINGO Model presents ‘Guiding Principles’ on which to ground enhancement initiatives towards quality results and business excellence. Related to the BASERA-MWENJE model, the aim in the SHINGO Model is to initiate organisations into adopting QMSs.
The WILGOR Framework, SHINGO Model and MaCoTra model emphasise the significance of culture and people in executing improvement initiatives. This is echoed in the BASERA-MWENJE in Steps 1, 2, 3, 5 and 6, where people and culture are shaped from strategic management, employee skills and qualifications, employees organised into work groups/teams and lastly the level of employee involvement in decision making at work. The MaCoTra Model highlights that transformation, which achieves results by requiring collaborative setting up of distinctive structures and systems. This is also highlighted in the Shingo Model and WILGOR Framework. The BASERA-MWENJE model also highlights the need for QMS structures in Step 3 (setting up quality department) and Step 7 (use of latest systems). The people are the nerve center of business operations; tools and systems alone do not operate a business, people do ( The Shingo Institute, 2021 ). The BASERA-MWENJE model application is in steps/stages like other models. It has 18 steps while the MaCoTra model has 7 steps (choruses) and the WILGOR Framework has 6 steps. The MaCoTra Model is shown in Figure 4 .
The Madzivire Collaborative Transformation (MaCoTra) Model
![quality hotels ltd case study quality hotels ltd case study](https://sciendo-parsed.s3.eu-central-1.amazonaws.com/6471bd88215d2f6c89daf54f/j_ejthr-2021-0021_fig_004.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20240902T204003Z&X-Amz-SignedHeaders=host&X-Amz-Expires=18000&X-Amz-Credential=AKIA6AP2G7AKHMOEQWMW%2F20240902%2Feu-central-1%2Fs3%2Faws4_request&X-Amz-Signature=f298ca0e8e347b82681e0da5f2e8011668ae8d3a28eda7cda48cb4f91b56e87b)
Critical success factors that are normally found in quality improvement initiatives are management involvement and organisational commitment, project selection, management and control skills, encouraging and accepting cultural change and continuous education and training (Basera, Mwenje, & Ruturi, 2019; Cagnazzo, Taticchi, & Brun, 2010). Management involvement and organisational commitment is underlined as it relates to the source of interest in adopting QMSs. The BASERA-MWENJE model asserts that success in adoption of QMS is achieved if management has a fundamental cause of motivation; the model being enforced from outside will not work. This is depicted in Step 1 through Step 8, which are all internal factors. This motivation should be passed on to all workers through their buy-in in vision, mission and goals of the organisation (strategic management).
Nevertheless, there were some differences with the BASERA-MWENJE model found in literature and in application in relation to other models. The models used different expression in wording and order of steps of its implementation, from the WILGOR Framework and MaCoTra Model. The BASERA-MWENJE model, just like MaCoTra model and WILGOR Framework, takes communication as a building block towards successful adoption of quality improvement initiatives. Worley and Doolen (2006) brings in the ‘chicken and egg argument’, stating that implementation of lean-in manufacturing resulted in improved communication. In their study they noted results with improved communication with first line workers and also noted poor communication outcomes with adoption of lean strategies. Worley and Doolen's conclusion makes it difficult as founded in BASERA-MWENJE model and hence the BASERA-MWENJE steps of QMS adoption step 6 – communication is challenging. Efficient communication and decision making is a key internal factor that can be used as a model building block which can improve adoption of QMSs in organisations. The BASERA-MWENJE model shows the internal factors and external factors in adoption of QMSs, while the MaCoTra model and WILGOR Framework do not classify their building blocks. The BASERA-MWENJE model is holistic while the MaCoTra transformative agenda and WILGOR Framework are internally focused.
Model construction is particularly well situated to new research areas for which existing theories seem inadequate. This article gives pragmatic evidence on the factors contributing to late adoption of QMSs in the hotel industry in Zimbabwe. Using concepts established from preliminary related literature analysis, the key factors and emergent factors were established.
Eisenhardt's Model of Building Theory from case studies was successfully applied in this study. A multiple case study of 9 hotels was conducted. A model surfaced that led to the construction of the BASERA-MWENJE model of QMS adoption. The model meets the tests of good theory or concept development (parsimony, testability, logical coherence) and is grounded in convincing evidence ( Redmond, 2015 ). The model consists of the BASERA-MWENJE steps to adopting QMSs. The model was corroborated by related literature and by contrasting it with other models. The BASERA-MWENJE model of QMS adoption borrows the Ubuntu value in naming the model, as it combines the surnames of the researchers, Basera meaning ‘something given as extra’ and Mwenje meaning ‘light’, thus BASERA-MWENJE meaning ‘extra light’.
The authors recommend that the implementation of the BASERA-MWENJE model of QMS adoption be tested in the hotel industry and also in other industries. For better implementation of the model, a multi-stakeholder approach is recommended. The BASERA-MWENJE model can be used at the national level to ensure the attainment of Vision 2030 -’Towards a Prosperous and Empowered Upper Middle-Income Society’ under the National Development Strategy. Adoption of QMSs by organisations improves their market competitiveness and ultimately improves the state of the economy.
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An Examination of Quality Management in Luxury Hotels
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The purpose of this case study was to analyze and compare the total quality management (TQM) practices of three luxury hotels. Leadership, guest and market focus, and information and analysis emerged as the three most significant TQM factors successfully implemented in these three hotels. The human resource focus factor was less successfully integrated into these hotels' operations. Although the three hotels claimed that they managed their processes effectively, these processes were not as well-designed or complex as in many other quality-conscious companies. Strategic planning emerged as one of the most difficult factors to implement. The general managers interviewed argued that these six factors contributed positively to their hotel's business results. Managerial and research implications are also discussed.
- Quality management
- total quality management
- Malcolm Baldrige National Quality Award
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Please note you do not have access to teaching notes, evaluating service quality in a uk hotel chain: a case study.
International Journal of Contemporary Hospitality Management
ISSN : 0959-6119
Article publication date: 1 October 2004
Service quality is a growing concern for many service firms in the UK. Today service firms are paying more attention than ever to the needs and expectations of the customers by consistently improving the quality of service provided to their customers. This paper briefly explores the relation between service quality and business performance followed by an assessment of service quality as a framework. The case study focuses on a hotel group in UK, where service quality was measured at six different locations. The findings from the research unveiled that there were significant variations for service quality between the six hotels.
- Customer services quality
- Hotel and catering industry
- Case studies
- United Kingdom
Antony, J. , Jiju Antony, F. and Ghosh, S. (2004), "Evaluating service quality in a UK hotel chain: a case study", International Journal of Contemporary Hospitality Management , Vol. 16 No. 6, pp. 380-384. https://doi.org/10.1108/09596110410550833
Emerald Group Publishing Limited
Copyright © 2004, Emerald Group Publishing Limited
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Utilization of machine learning and hyperspectral imaging technologies for classifying coated maize seed vigor: a case study on the assessment of seed dna repair capability.
![ORCID quality hotels ltd case study](https://pub.mdpi-res.com/img/design/orcid.png?0465bc3812adeb52?1724941758)
1. Introduction
2. materials and methods, 2.1. sample preparation and hyperspectral image acquisition, 2.2. ground truth annotation: seed vigor classifications, 2.3. data preprocessing, 2.4. ml model development, 3.1. seed vigor classification, 3.2. oversampling algorithm performances, 3.3. ml model performances, 4. discussion, 5. conclusions, author contributions, data availability statement, acknowledgments, conflicts of interest, abbreviations.
ADASYN | Adaptive synthetic algorithm |
AI | Artificial intelligence |
ANOVA | Analysis of variance |
AUC | Area under the curve of the cumulative radicle emergence fitted curve |
BorderlineSMOTE | Borderline synthetic minority oversampling algorithm |
BP | Between-paper technique |
CARS | Competitive adaptive reweighted sampling |
CNNs | Convolutional neural networks |
DL | Deep learning |
DNA | Deoxyribonucleic acid |
HIS | Hyperspectral imaging |
LDA | Linear discriminant analysis |
MCC | Matthews correlation coefficient |
MGT | Mean radicle emergence times |
ML | Machine learning |
MSC | Multiplicative scatter correction |
PCA | Principal component analysis |
PLS-DA | Partial least squares discriminant analysis |
RE | Radicle emergence |
REMax | Maximum radicle emergence |
ROC | Receiver operating characteristic |
ROI | Region of interest |
SG | Savitzky–Golay |
SNV | Standard normal variate |
SVM | Support vector machine |
T50 | Radicle emergence speed |
U7525 | Uniformity of radicle emergence |
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Click here to enlarge figure
Class Label | Number of Data in the Training Set | Number of Data in the Validation Set | Number of Data in the Test Set |
---|---|---|---|
(75%) | (15%) | (10%) | |
High-vigor seed lot | 6858 | 1372 | 914 |
Low-vigor seed lot | 1323 | 265 | 176 |
Total | 8181 | 1637 | 1090 |
Pretreatment | OG | SNV | MSC | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Wavelength Selection | None | CARS | None | CARS | None | CARS | |||||||
Oversampling Technique | None | None | ADASYN | Borderline SMOTE | None | None | ADASYN | Borderline SMOTE | None | None | ADASYN | Borderline SMOTE | |
ELDA | Accuracy | 95.05 | 97.07 | 98.08 | 98.49 | 95.14 | 97.48 | 97.02 | 94.91 | 97.80 | 97.75 | ||
Sensitivity | 95.50 | 96.95 | 99.72 | 99.89 | 94.58 | 98.73 | 98.56 | 94.66 | 98.63 | 98.84 | |||
Specificity | 95.39 | 97.77 | 90.66 | 92.11 | 99.24 | 91.42 | 89.66 | 96.68 | 93.65 | 92.45 | |||
Precision | 99.28 | 99.61 | 97.96 | 98.29 | 99.89 | 98.24 | 97.85 | 99.50 | 98.73 | 98.46 | |||
F1-score | 97.10 | 98.26 | 98.83 | 99.09 | 97.16 | 98.48 | 98.21 | 97.02 | 98.68 | 98.65 | |||
MCC | 0.8133 | 0.8918 | 0.9343 | 0.9483 | 0.8180 | 0.9103 | 0.8945 | 0.8080 | 0.9207 | 0.9199 | |||
SVM | Accuracy | 97.25 | 94.73 | 99.13 | 99.08 | 97.66 | 99.45 | 99.45 | 97.02 | 99.31 | 99.27 | ||
Sensitivity | 96.91 | 94.05 | 99.40 | 99.34 | 97.27 | 100 | 99.89 | 96.55 | 99.89 | 99.89 | |||
Specificity | 99.35 | 100 | 97.78 | 97.78 | 100 | 96.91 | 97.31 | 100 | 96.53 | 96.28 | |||
Precision | 99.89 | 100 | 99.56 | 99.56 | 100 | 99.34 | 99.45 | 100 | 99.28 | 99.23 | |||
F1-score | 98.37 | 96.93 | 99.48 | 99.45 | 98.62 | 99.67 | 99.67 | 98.24 | 99.59 | 99.56 | |||
MCC | 0.8990 | 0.8021 | 0.9686 | 0.9669 | 0.9146 | 0.9807 | 0.9805 | 0.8905 | 0.9757 | 0.9742 |
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Wonggasem, K.; Wongchaisuwat, P.; Chakranon, P.; Onwimol, D. Utilization of Machine Learning and Hyperspectral Imaging Technologies for Classifying Coated Maize Seed Vigor: A Case Study on the Assessment of Seed DNA Repair Capability. Agronomy 2024 , 14 , 1991. https://doi.org/10.3390/agronomy14091991
Wonggasem K, Wongchaisuwat P, Chakranon P, Onwimol D. Utilization of Machine Learning and Hyperspectral Imaging Technologies for Classifying Coated Maize Seed Vigor: A Case Study on the Assessment of Seed DNA Repair Capability. Agronomy . 2024; 14(9):1991. https://doi.org/10.3390/agronomy14091991
Wonggasem, Kris, Papis Wongchaisuwat, Pongsan Chakranon, and Damrongvudhi Onwimol. 2024. "Utilization of Machine Learning and Hyperspectral Imaging Technologies for Classifying Coated Maize Seed Vigor: A Case Study on the Assessment of Seed DNA Repair Capability" Agronomy 14, no. 9: 1991. https://doi.org/10.3390/agronomy14091991
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