MANAGER’S PERCEPTION TOWARDS SECURITY MANAGER’S PERCEPTION TOWARDS SECURITY FACTORS: A COMPARATIVE EXAMINATION OF FACTORS: A COMPARATIVE EXAMINATION OF

3 TO 5 STAR HOTELS IN NAIROBI AND 3 TO 5 STAR HOTELS IN NAIROBI AND MOMBASA COUNTIES, KENYAMOMBASA COUNTIES, KENYA

VINCENT NYAMARI MARANGA, M.Sc. (K.U)VINCENT NYAMARI MARANGA, M.Sc. (K.U)REG.NO.N85/11281/06REG.NO.N85/11281/06

SUPERVISORS:SUPERVISORS:

Dr. Rosemarie Khayiya (Ph.D)Dr. Rosemarie Khayiya (Ph.D)Department of Hospitality ManagementDepartment of Hospitality Management

Dr. Linda Musumba (Ph.D)Dr. Linda Musumba (Ph.D)School of LawSchool of Law

Kenyatta UniversityKenyatta University1

The Effects of Paradise Hotel Bombing; (2002)

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i. Decrease in tourist arrivals;ii. Significant increase in unemployment; iii. Decline in Foreign Direct Investment (FDI);iv. Divergence of Government resources;v. Financial cost continues to escalate.

i. The hotel industry is a soft target with high human flow traffic;

ii. Anybody with bargaining power becomes a guest;

iii.Deals with both international and domestic guests;

iv.Real and perceived attacks;

v. Relaxed security personnel.

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a) Commonalities between the lack of a unified hotel security standards and policy framework (Kanold, 2011);

b) East African Community (EAC) guidelines on hotel standards have failed to address insecurity issues (United Nations World Tourism Organization, 2007);

c) Shifted their strategy on security efficiency in their operations to enhance their competitiveness (Wadongo et al., 2010);

d) In 2008, due to Post Election Violence, Kenya lost at least sh15 billion due to the travel advisories;

e) The loss negatively affected almost all economic sectors and specifically the Gross Domestic Product by 2% (Kenya Tourist Board, 2009);

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a) Rankings of Kenya by Travel & Tourism Competitive Index on safety and security concerns globally was 121/131 in 2009 and 135/140 in 2013 (United Nations World Tourism Organization (UNWTO), 2009),;

b) Porous borders and extensive coastline makes it difficult to accurately monitor and mitigate security threats (UNWTO, 2007);

c) Insecurity is a threat to local and international investors in East Africa with some firms spending up to 7% of total revenues (Government of Kenya, 2007);

d) Partnership of United States and Government of Kenya in combating security issues, rampant reported crimes within hospitality facilities (Kanold, 2011);

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a) To determine the indicators of vulnerability of the hotel facilities towards insecurity;

b) To find out the current hotel standards of security within the hotel facilities;

c) To evaluate the effects of insecurity on the hotels’ performance;

d) To profile crime trends and security threats in the hotel industry.

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a) Ho1: A direct negative relationship exists between investment in security management systems and high guest turnover in the hotel industry;

b) Ho2: Security training does not significantly influence appropriate security measures taken in the hotel industry;

c) Ho3: Security lapses in procedure and policy do not significantly contribute to Hotel’s vulnerability.

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i. Generalization beyond these regions was done with caution.

ii.Descriptive cross-sectional survey was used hence changes in security issues over time were not considered

Research Design

A descriptive cross-sectional comparative survey design was adopted

Study Area

Why these regions?

Nairobi and Mombasa

Each category of all listed hotels ranging from 3-5 stars can at least be found in both regions;Nairobi- Targets business and transit tourists;Mombasa- Targets Leisure holiday tourists

Hotel GM, Hotel security managers, Division Room managers, Front Office managers,

Other stakeholders

KTB, Kenya Tourist Police, Kenya Hotelkeepers Association, Provincial Security Committee, Ministry of Tourism and information and Kenya Navy.

Target Population

32 hotels (160 respondents) 26 hotels accessed from a target of 32 hotels 87% Response Rate 9

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a) EDA (Exploratory Data Analysis), For evaluation of outliers and any missing cases;

b) Means, %s, Sd. & frequencies, To describe quantitative data and findings presented in summary tables and graphs;

c) Independent Sample T-test for Equality of Means, For measuring the differences on crime trends between Hotels in Nairobi and Mombasa;

d) Regression Analysis & Structural Equations Modeling (SEM), To determine the relationship between the dependent variable (hotel security competitiveness) and the independent variables;

e) Odds Ratios (OR) and its associated 95% Confidence Interval (CI), To identify the factors that are more likely to explain the hotel insecurity and P-value <5% was considered statistically significant;

f) Content Analysis; To analyze qualitative data according to themes and Patterns

Independent Variables

Indicators of insecurity•Robberies•Theft•Injuries and deaths

Effects of insecurity•Low bookings•loss of revenue•Increased costs

Security Standards•Quality•Availability•Effectiveness

Dependent variableIntervening

variable

Crime Trends•patterns of crime

Hotel Destination

Security

Hotel performance Competitiveness•Increased Revenue•Increased Bookings •Customer Satisfaction

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OBJECTIVE 1: Indicators of Vulnerability of the Hotel facilities towards insecurity

a) The age of the hotels did not affect significantly the security levels which implied that other factors might be the cause of diminishing security standards;

b) Inconsistent with the research carried out by the Center for Hospitality Research (2009) which stated that the best safest and secure hotel is the one that is less than 7 years old and worst security rating is the one over 20 years old.

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Cross-tabulation between Security Vulnerabilities in hotels and Property Age

Comparison of Security Vulnerabilities in Hotels by Region

a) An independent sample T-test was conducted to establish if there was a significant difference of scores of insecurity variables between Nairobi and Mombasa. Mombasa was likely to be more vulnerable to insecurity threats than Nairobi, however this was not statistically significant (p=0.563).

b) Consistent with research carried out by Bado (2012) which states that the high levels of insecurity in the coastal region in 2011 badly affected tourism investment.

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Objective 2: Current Security Standards within the Hotel facilities

Distribution of Security Measures in hotels by Region

a) Nairobi had 66.7 % surveillance cameras while Mombasa had 33.3 %. The implication of these findings is that hotels in Nairobi have better functional security devices and Preparedness than hotels in Mombasa.

b) Concur with a similar study carried out in United Kingdom by (Samantha, 2004) which indicated that 74 % of the UK hotels are failing to carry out security checks on guests. 15

Frequency of Security Training In Hotels by Region

a) A significant difference between training on security issues across the two regions with Mombasa doing it more frequently as compared to Nairobi (p value<0.001).

b) The implication of this finding is that hotels in Mombasa were likely to be under security threat than hotels in Nairobi.

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Cross-tabulation of frequency of Security Training Versus Security Measures in the hotel industry

a) No significant association between training on security and the measures applied by the hotels (p value = 0.198) A gap between the training and the application of the security procedures in the hotels.

b) No sufficient evidence that the training did not promote security measures taken in the hotel industry.

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Objective 3: Evaluation of the effects of insecurity on the hotels’ performance

a) In 3 star hotels, Nairobi spends more by 56 % than Mombasa. In the five star category, cost of security was equally similar. The implication is that high end establishment have not only invested more but are security concerns.

b) Consistent with the GoK’s Vision 2030 which states that firms spends up to 7% of their revenue on security costs.

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MombasaNairobi

Region

15000000

12000000

9000000

6000000

3000000

0

Co

st o

n S

ec

urit

y

7

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a) The Nairobi invested more than Mombasa hotels. however, two hotels in Mombasa are chain affiliated with similar security standards with Nairobi.

b) A correlation and simple linear regression was undertaken on the hypothesis which states that a direct positive relationship exists between investment in security management systems and high guest turnover in the hotel industry (see following slide)

Box plot showing the variation of security costs in the regions

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Correlation and Simple Linear Regression

a) Both regions had a positive correlation between occupancy and security costs at 0.12 and 0.30, however, this was not statistically significant. It had a weak correlation (p value > 0.05). The investment in security were not replicated into the hotel increase in occupancy.

b) This might be a short cyclic event which might need time to observe the results of investment . Maybe this is along term effect.

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Objective 4 :Profiling Crime Trends and Security Threats in the hotelindustry by star rating

a) In the three star hotels 56 % (theft) 69 % (drug trafficking) while 53% (prostitution) respectively. In the four star hotels 69% (theft) It is important to note that all the four star hotels were found at Mombasa according to the Kenya Gazette of 2003 Hotels and Restaurant classification.

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Prostitution

a)Mombasa had more severe cases of security threats than Nairobi. In Mombasa region, 69.2 % had drug trafficking, while 57.9 % and 52 % had prostitution and theft respectively.

b)In Nairobi, 48 % and 42.1 % had theft and prostitution respectively. However, 30.8 % had cases of drug trafficking. This findings is consistent with the sentiments by Sindiga (1999) and Kibicho (2004 b) that the coastal region has become a favorite destination for sex tourists mainly due to lack of policy guidelines to control it.

Profiling Crime Trends and Security Threats in the hotel industry by region

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Table 4.6. Factor Analysis on Room Division Manager on concern for Security Issues

Component

Initial EigenvaluesRotation Sums of Squared

Loadings

Total% of

VarianceCumulati

ve % Total% of

VarianceCumulati

ve %1:Intra-hotel factor

10.907 54.536 54.536 5.111 25.555 25.555

2: Robbery and Burglary

2.261 11.304 65.841 4.441 22.206 47.761

3: Injury and Fraud

1.793 8.963 74.803 3.293 16.464 64.225

4: Theft and Carjacking

1.508 7.539 82.343 2.946 14.729 78.954

5: Facility Default 1.041 5.206 87.548 1.719 8.594 87.548

Room Division Manager on concern for Security Issues

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Table 4. 8. Factor Analysis for the Front Office Manager on Security Issues

Total Variance Explained

Component

Initial EigenvaluesExtraction Sums of Squared Loadings

Total% of

VarianceCumulativ

e % Total

% of Varianc

eCumulati

ve %1. Hotel Vulnerabilities

6.557 72.856 72.856 6.557 72.856 72.856

Note. Extraction Method: Principal Component Analysis.

Front Office Manager Concern for Security Issues

The hotels in Nairobi were less vulnerable than hotels in Mombasa. investors have invested more in high- end establishments

The age of the hotel did not affect security levels of the establishments; other factors might be the cause of deteriorating security factors.

The hotels that are safe and secure are those less than 7 years old and worst security rating are those over 20 years old.;

The quality, security, age and occupancy rate of hotel are potential factors affecting the costs for operating and maintaining the hotel premises.

The outsourcing of security services has its own challenges to both the hotel staff as well as guests. Most of the hotels employ unprofessional security personnel;

There was significant difference in training on security issues across the two regions with Mombasa doing it more frequent compared to Nairobi (p value<0.001);

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The age of the hotels is not a determinant factor that affects the security but a multiplicity of factors ;

A fundamental gap between hotel security and the Kenyan police security, therefore the training should commensurate to the needs of the hotel industry;

need to capacitate the security guards to be able to expand their scope of security within the hotel industry;

Hotels to continually develop security strategies to meet the evolution of security challenges in the industry;

Legalize special security agencies within the hotel and tourism industry to deal with terrorism acts

A uniform platform of security procedures in the hotel industry to be consistent with stipulated internationally security standards;

There is need for the hotel industry to comply with the use of biometrics in all hotels to improve security;26

A similar study also needs to be carried out on other accommodation sectors;

A study needs to be done on the role of private security services in the hotel industry;

A study needs to be carried out on the safety of guests in the hotel industry;

A study needs to be done on the recruitment and selection of security personnel in the hotel industry;

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THANK YOU FOR YOUR KIND ATTENTION

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