Effects of crisis management on hotel performance .pptx

Effects of crisis management on hotel performance
A study of hotels in Mombasa kenya

1. EFFECTS OF CRISIS MANAGEMENT PRACTICES ON PERFORMANCE OF HOTELS IN MOMBASA COUNTY EUNICE MUKOLWE ADMISSION NO. STHE/DPHIL/H/006/16 6/12/2023 1 Supervisors Dr . Dorothy Rotich Dr . Isabella Cheloti-Mapelu Prof. Hellen Ipara

2. BACKGROUND OF THE STUDY Crisis events seriously threaten the survival and development of hotels, and assessing the impact of crises mgt practices on hotels is crucial for them to develop effective response and recovery strategies. The Tourism and Hospitality industry could be described as a volatile and fragile industry( Speakman , 2011). A key element of success or failure is a tourism destination ability to provide a safe, predictable and secure environment for its visitors. However as noted by Xu and Grunewald (2009) safety and security can be compromised in the form of crises which can arrive without warning and often cause immense tangible and intangible damage to tourism destinations. As a result of their feeling of insecurity, potential tourists may decide not to visit the affected destinations, consequently affecting the hospitality ind.

3. CONT … The issue of how hospitality org can maintain good perf when faced with such critical situations has largely remained unexplored . The susceptibility of tourism destinations to crises is widely addressed in literature . Faulkner argued that a lack of systematic research in the field analyzing the impacts of crisis events and industry responses meant that destinations were unprepared to respond effectively when confronted with a crisis situation . Studies by Speakman (2011), Hystad and Keller (2008 ), Glaesser (2006) Beirman (2003 ) and Faulkner (2001) suggest that majority of tourism and hospitality businesses do not actively incorporate crises mgt strategies and practices into their business which may consequently lead to – ve perf .

4. CONT .. Few studies that evaluated what hotel managers do during or immediately after a crisis: Israeli and Reichel (2003) on the hosp industry in Israel; Okumus and Karamustafa (2005) on the Turkish hosp industry and Israeli et al. (2011) in the Indian luxury hotel industry . The authors constructed a list of crisis mgt practices, evaluated the importance mgrs assign to each practice and also the level to which mgrs use each practice. These studies however did not assess the effect of these crisis mgt practices on performance of the hotels. Given the vulnerability scale for the country .This study sought to investigate cases in which various events lead to a downturn in consumption and travel which, in turn, result in a crisis in the hospitality industry.

5. Statement of the Problem As the global economy moves from a manufacturing economy towards a service economy, the study of CM is crucial as over reliance on revenue from the hospitality industry can be devastating, as lost revenue contributes to a downward economic trend and increased unemployment. (Kasarvuran,2020) The way, a hotel manages its recovery during and after a crisis plays a significant role in how well it emerges from a crisis. Frequent crisis events on hotels is eroding the confidence of prospective tourists thereby causing anxiety in the hospitality industry. Crisis events around the globe such as Twin tower bombing in America, the Bali bombings in Indonesia in 2005 , attacks in Manchester uk 2019 and Nice France 2020. Terror attacks in Kenya include, the US embassy bombing in August 1998, Mombasa Paradise Hotel bombing in Nov 2002, several grenade attacks from 2011 to 2013, police ambushes in the northern part of Kenya, Westgate mall attack in Sept 2013 and the Garissa University attack. Wild fires in Australia, California,Greece,Portugal ,Spain etc

6. CONT.. Hotel fires in Watamu’s Mbuyu lodge and Barracuda resort 2023, south coast Tiwi Beach resort,Palm hotel 2016. Disease pandemic e.g SARS and Covid 19 Subsequently , Potential visitors may not travel or travel elsewhere due to safety concerns. In addition, Kenya has witnessed a slump in the number of tourists visiting its national parks, sandy beaches and accommodation facilities due to a adverse travel advisories issued against it, especially 2 Mombasa by various countries such as Canada, Australia, America, France and UK thus posing a major economic crisis in the hosp sector. (New tourism strategy for Kenya 2021-2025) In light of these potentially damaging events and their increasing frequency, tourist destinations such as Kenya must put in place effective CMP to maintain and restore visitor confidence after a crisis event.

7. JUSTIFICATION FOR THE STUDY In any org the impact of crisis events on organizational perf cant be overemphasized, it affects everything that the org stands for (Olawale,2014). Crisis mgt is aimed at creating a conducive atmosphere where business can thrive and be profitable. However, the inability of managers to successfully resolve a crisis may have - ve effect on productivity level, stagnation in operational activities, reduced proficiency, inability to meet stated targets, decrease in sales level etc . Kenyas Coast has seen a decline in tourist numbers and a steady loss of market share to peers such as Zanzibar ,developing proactive crisis mgt strategies is critical.(New tourism strategy for kenya 2021 -2025) Crisis managed with levity by a hotel might lead to closure of such hotels if appropriate crisis management practices are not devised to avert the situation within the shortest time. A crisis mind set is important .

8. GENERAL OBJECTIVE T o determine the effects of crisis management practices on performance of hotels in Mombasa County, Kenya. 6/12/2023 8

9. 1.3 Research Objectives To determine key practices used in crisis management in the hotels in Mombasa County. To establish the effects of human resource crisis management practices on performance of hotels in Mombasa County. To determine the effects of marketing crisis management practices on performance of hotels in Mombasa County. To examine the effects of maintenance crisis management practices on performance of hotels in Mombasa County. 1.3.1 RESEARCH QUESTION 1. What key practices are used in CM in hotels in Mombasa County. 2.What is the effect of government CMP on performance of hotels in Mombasa County ?

10. 1.4 HYPOTHESIS H 1: Human resource crisis management practices have no effect on organizational performance. H 2: Marketing crisis management practices have no effect on organizational performance. H 3: Maintenance crisis management practices have no effect on organizational performance.

11. THEORETICAL FRAMEWORK CONTINGENCY THEORY According to contingency perspective, there is no single best model/practices to restore a hospitality org after a crisis (Mansour, 2013). The crisis practices that are effective in some situations may not be successful in others (Ping, Cui, & Pan, 2011). However, the optimal CMP is dependent on situational appropriateness. To be exact, the crises facing hospitality sector are unique and require a tailored approach . CHAOS THEORY In contrast to traditional crises management frameworks, chaos theory views systems, such as the tourism and hospitality as being unstable, non-linear and totally unpredictable. This sentiment hold true for a hotel as a system and the unpredictability of crises events .

12. CONT .. Chaos describes a situation where a system is dislodged from its steady state condition by a triggering event which is as random and unpredictable as the outcome. It involves the regrouping of the elements of the system, from which a new order eventually emerges . (Faulkner and Russell, 1997 ) According to Speakman (2011), chaos theory offers a more appropriate theoretical framework from which to study the management of crisis. In particular, various key elements exist within chaos theory which, if recognized as they appear in a crisis in the hospitality industry, can provide suitable moments for managerial intervention. Ritchie (2004), stresses that chaos theory could provide managerial insight in times of crisis in the tourism and hospitality industry . ELEMENTS OF CHAOS THEORY Edge of chaos…butterfly effect Bifurcation and cosmology Self organization and strange attractors

13. CONCEPTUAL FRAMEWORK 6/12/2023

14. METHODOLOGY Study Area : Mombasa County Research Paradigm : Pragmatism Research Design : Descriptive Survey And sequential exploratory design Target Population : 580 hotel management staff Sample size : 231 hotel management staff Sampling technique: Purposive, Stratified and simple Random Sampling Data Collection Instruments : Questionnaires And Interview Schedules Reliability: Cronbach alpha [email protected] Validity: Face , content, construct convergent tested using factor analysis. Variables with loadings above .5 were retained for further analysis( polit &Beck,2006) Data Analysis: Descriptive , SEM , thematic analysis Ethical consideration: Informed consent, confidentiality and privacy, researchers responsibility

15. MEASUREMENT OF VARIABLES Organizational performance (endogenous latent variable) 4 indicators; financial , customer, learning and internal business process ( adopted from Kaplan and Norton,1996 balanced scorecard ) Human resource crisis management practice ( exogenous latent variable ) 6 indicators : reduction in labour force; giving unpaid vacations, reduction in number of working days; reduction in pay rate; replacement of long tenure employees and outsourcing human resources . M arketing crisis management practice (exogenous latent variable) 8 indicators : Joint marketing campaigns, media adverts; price cuts on services; marketing and promotions of new services; marketing to new segments, change in menu offerings; and extensions of business menu hours. M aintenance crisis management practice ( exogenous latent variable) 5 indicators: limiting services in the restaurant, postponement of systems maintenances; use of less expensive kitchen substitutes and postponement of scheduled payment . (adopted from Israel and Reichel,2003). 6/12/2023 15

16. Univariate outliers : used skewness and kurtosis and box plots-no cases detected Multivariate outliers : used Mahalanobis distance statistics. 9 cases 16 RESULTS : RESPONSE RATE Number % Total questionnaire distributed 219 100 Total returned questionnaires 207 94.5 Unusable questionnaires 12 0.05 Usable questionnaires 198 90.4

17. 6/12/2023 17 RESULTS : DEMOGRAPHIC INFORMATION Frequency Percent Gender Male 81 40.9 Female 117 59.1 Total 198 100 Age in years 18-25 years 64 32.3 26-40 years 117 59.1 Above 40 years 17 8.6 Total 198 100 academic qualification None 1 0.5 Primary 10 5.1 Secondary 129 65.2 College 58 29.3 Total 198 100 job title Supervisor 37 18.7 Ass. Manager 29 14.6 Manager 18 9.1 Other 114 57.6 Total 198 100 Duration of employment Below 5 years 106 53.5 6-10 Years 48 24.2 Above 10 years 44 22.2 Total 198 100 Department Housekeeping 51 25.8 Front Office 49 24.7 Food and Beverages 80 40.4 Other 18 9.1 Total 198 100

18. 6/12/2023 18 RESULTS : CRISIS INCIDENTS IN THE HOTEL Has the hotel experienced any crisis? Frequency Percent Yes 184 92.9 No 14 7.1 Total 198 100

19. 6/12/2023 19 RESULTS: Various Crisis Experienced by the Hotel Frequency Percent Terrorism 10 5.1 Covid 19 184 92.9 Floods 2 1 Fires 1 0.5 Others 1 0.5 Total 198 100

20. Factor and reliability analysis 20 RESULTS : EXPLORATORY FACTOR ANALYSIS Findings showed KMOs were more than 0.5, hence data was adequate and good to be subjected for factor analysis (Leech et al., 2013). All Bartlett's tests were significant at p-value < 0.05, indicating the items of all variables were suitable for measuring the variables with equal variance, items were related. Total variance explained showed all cumulative variances were above 40% indicating that the items were measuring the variables and were able to provide original data for each variable Further , items with high factor loading scores of above recommended value of 0.05 were retained for further analysis (Hair et al., 2014) Variable KMO Bartlett's Test Cumulative % Loadings No. of components Hotel Performance 0.771 702.228 * 64.902 > 0.5 4(OP1, OP2, OP3, OP4) Human Resources Crisis Management 0.912 1096.87 * 80.149 > 0.5 2(HRC1 HRC2) Marketing Crisis Management Practices 0.704 466.39 * 57.135 >0.5(1 item dropped ) 3(MCM1 MCM2 MCM3) Maintenance (Cost-Cutting) Crisis 0.595 767.382 * 65.262 > 0.5 4(MainCM1 MainCM2 MainCM3 MainCM4)

21. Factor and reliability analysis 21 RESULTS : DESCRIPTIVE STATISTICS: ORG PERFORMANCE n=198 Mean Std. Dev Skewness Kurtosis High profit level in relation to expectations 2.83 0.95 0.48 -0.47 High profit level in relation to competitors 3.01 0.82 -0.18 1.49 Increase in customer loyalty 3.15 0.85 0.55 0.55 Acquisition of new customers 3.15 0.95 0.20 -0.61 New market growth 3.28 1.31 0.03 -1.37 Employment of competent personnel 3.21 1.08 -0.45 -0.37 Increase in occupancy rates 2.64 0.97 0.28 -0.07 Increase in perceived customer satisfaction 3.23 0.89 -0.55 -0.26 Increased average room rate 2.26 1.03 0.59 -0.35 Development of new products 2.89 1.21 -0.20 -0.99 Improved productivity 3.09 1.00 0.30 -0.69 Effectively responding to changes in the market 3.84 1.36 -0.74 -0.93 Hotel Performance 3.05 0.61 -0.16 -0.17

22. Factor and reliability analysis 22 RESULTS : DESCRIPTIVE STATISTICS : HUMAN RESOURCE CMP n=198 Mean Std. Dev Skewness Kurtosis We reduce the labor force by laying off employees 2.737 1.123 0.207 -0.786 We use unpaid leave to reduce labor force 2.717 1.251 0.141 -1.105 We reduce the number of working days per week 2.783 1.305 0.036 -1.339 We reduce employee pay 2.571 1.338 0.091 -1.389 We replace highly paid employees with new low paid employees 2.500 1.431 0.404 -1.268 We rely on outsourced staff 2.576 1.364 0.391 -1.097 Reduced number of hours worked 2.894 1.284 0.011 -1.231 Human Resources Crisis Management Practices 2.683 1.110 0.209 -1.515

23. Factor and reliability analysis 23 RESULTS :MARKETING CRISIS MANAGEMENT PRACTICES n=198 Mean Std. Dev Skewness Kurtosis We market together with other merchants and hotels 3.293 1.092 -0.179 -0.079 We advertise in the media i.e. television, radio, newspapers, social media 4.182 1.103 -1.675 2.312 We give special offers 4.333 0.878 -1.478 2.287 We reduce our prices 4.207 0.903 -1.509 2.587 We market new services and products 3.944 0.862 -0.421 -0.539 We Market to domestic tourists and locals 3.697 1.166 -0.340 -0.947 We change the menu 4.030 1.032 -0.705 -0.504 We employ a destination specific marketing strategy 3.869 0.920 -1.239 1.916 We Market to foreign tourists with specific focus on the hotels’ distinctive features and relative safety 3.712 1.299 -0.643 -0.759 Marketing Crisis Management Practices 3.919 0.624 -2.089 4.358

24. Facd reliability analysis 24 RESULTS: MAINTENANCE CRISIS MANAGEMENT PRACTICE n=198 Mean Std. Dev Skewness Kurtosis We cut costs by reducing the services offered by the hotel e.g. gym, spa, restaurant etc. 2.394 1.245 0.428 -0.725 We Postpone major expenditures on hotel renovation 2.258 1.278 0.935 -0.048 We cut costs by postponing cosmetic maintenance to the hotel 1.843 1.145 1.439 1.259 We cut costs by postponing systems maintenance 1.636 0.906 1.406 1.460 We cut cost by using less expensive substitutes in the kitchen 2.217 1.325 0.758 -0.711 We postpone scheduled payments 2.424 1.206 0.715 -0.373 We eliminated non-essential expenses 3.500 1.112 -0.728 0.055 We cut capital expenditure 2.990 1.266 -0.329 -0.974 We used take away services 2.015 1.296 0.819 -0.826 We imposed salary cuts for staff 3.177 1.300 -0.557 -0.822 We temporarily suspended operations 3.596 1.301 -0.890 -0.216 Negotiation with suppliers to lower costs for foodstuff 4.535 0.822 -1.884 3.385 Maintenance (Cost-Cutting) Crisis Management 2.728 0.441 0.735 3.972

25. Factor and reliability analysis 25 RELIABILITY AND VALIDITY TESTS Exogenous and endogenous variables Latent variables Factor Loadings (>0.6) CVA (>40%) R eliability (Cronbach alpha) CR (>0.7) AVE (>0.5) O P O P1 0.662 56.664 0.736 0.857 0.601 O P2 0.819   O P3 0.804           O P4 0.710         HRCMP HRC1 0.912 83.187 0.797 0.713 0.555 HRC2 0.912     MCMP MC1 0.897 74.138 0.834 0.896 0.742 MC2 0.864 MC3 0.821 MainCMP MainC1 0.895 80.918 0.820 0.944 0.809 MainC3 0.879 MainC2 0.903         MainC4 0.920

26. 6/12/2023 26 RESULTS : CFA MEASUREMENT MODEL Fit Indices (CFA) Measurement Model fit results χ2( df ) 68.762 (49), p=. 033 CMIN/ df 1.403 IFI . 984 TLI . 975 CFI . 984 GFI . 950 NFI . 948 RFI .917 PNFI . 616 RMSEA . 045

27. 6/12/2023 27 FINDINGS: CFA MEASUREMENT MODEL

28. 6/12/2023 28 RESULTS : SEM MODEL: GOODNESS OF FIT STATISTICS FOR FINAL SEM MODEL Fit Indices Final SEM Model χ2( df ) 78.128 (54), p=.018 CMIN/ df 1.447 GFI .943 NFI .941 RFI .915 IFI .981 TLI .972 CFI .981 PNFI .651 RMSEA .048

29. 6/12/2023 29 FINDINGS: FINAL SEM MODEL

30. R 2 = 37.1 ..total variation of hotel performance is explained by marketing crisis management, human resources crisis management and maintenance crisis management practices 30 FINDINGS: FINAL SEM MODEL: HYPOTHESES TESTING Estimate S.E. C.R. P RESULTS OP <--- MainCMP -.086 .033 -2.613 .009 Rejected OP <--- MCMP .155 .049 3.145 .002 Rejected OP <--- HRCMP .145 .053 2.715 .007 Rejected R   Squared 37.1      

31. 6/12/2023 31 RESULTS: Qualitative Analysis Of Government Crisis Management Practices Theme 1: Stimulus funds “There was government announcement on a stimulus package that will cover losses and expenses, however, am not sure if this was implemented since we did not receive even a coin”( 1-16 ) Theme 2: Emergency meetings “There were meetings held by Ministry of health official for training of frontline employee of our hotels, few employees were trained on how to use PPE kits and other precaution measures to take” (1-05 ) Theme 3: Tax relieve “government reduction of VAT and removal of income tax on workers who earn a maximum of 24,000 shillings was very beneficial to our employee who majority earn less than KSH 25000” (1-12 ) Theme 4: Aggressive Marketing Activities “Magical Kenya campaigns were everywhere. Same to tembea kenya campaigns. The ministry of tourism really tried to market the country during those difficult times. Terrible times”. (1-09)

32. CONCLUSION 6/12/2023 32

33. RECOMMENDATION 6/12/2023 33

34. 6/12/2023 34