An Investigationon Critical Success Factors of IT Outsourcing Satisfaction in Hong Kong Financial Service Industry across Organizations Demographics

This research aims to determine the critical success factors of IT outsourcing satisfaction across different demographic parameters. Based on the research findings, possible recommendations are proposed for exploring new IT outsourcing customers. To analyze the variables and demographics, a hybrid methodology combining both qualitative and quantitative approaches was utilized. This involved conducting both a focus group and a survey, resulting in a high response rate of 97% for data analysis. The IT outsourcing objectives of the organization and their ranking of importance were identified in the Hong Kong financial services industry (FSI). Recommendations are (1) Clearly Define Objectives, (2) Define Scope and Deliverables, and (3) Service Performance Monitoring suggested to increase the intention of IT outsourcing continuously. Using the snowball sampling method may have introduced potential biases into the information gathered. In future studies, assessing the scale of IT outsourcing projects more comprehensively would be beneficial. Employing a broader research scope would allow for a deeper understanding of the entire population, thereby aiding the industry in comprehending needs and formulating appropriate policies. This study adopts a comprehensive approach to pinpointing demographic segments associated with satisfaction in IT outsourcing within Hong Kong’s FSI. Furthermore, it offers practical suggestions to service providers on identifying target customers and fostering continued utilization of IT outsourcing. 

Introduction

Globalization has reshaped business operations, leading to increased interdependence among companies. This trend has placed significant pressure on organizations to enhance profitability and productivity. Outsourcing has become a key strategy for companies aiming to cut costs and boost competitiveness, productivity, and profitability (Taponen & Kauppi, 2020).

The widespread adoption of information technology (IT) has not only supported management but also provided a competitive edge. However, the growing strategic and operational reliance on IT has escalated expenses, making it a substantial part of businesses’ indirect costs (Altin, 2021). To manage these costs, companies often turn to IT Outsourcing (ITO), which is particularly vital in the financial services industry (FSI) due to rapid technological advancements over the past five years. Technologies like artificial intelligence (AI), big data, and machine learning have empowered the FSI to foresee risks, optimize investment strategies, and enhance fraud detection (Hussain, 2023). Developing these technologies in-house can be prohibitively expensive, making ITO a viable alternative that allows companies to concentrate on their core business.

Hong Kong’s IT industry is expected to grow significantly between 2021 and 2026, with an anticipated growth rate of 4.89% (Fitchsolutions, 2021; Mordorintelligence, 2021; Reogma, 2021; Technavio, 2022). This growth is driven by the rising demand for IT services such as data center management and cloud computing platforms. The Hong Kong IT market is projected to reach around USD 6.72 billion from 2021 to 2026 (Marketresearch, 2022; Technavio, 2022), with ITO expected to account for approximately USD 3.19 to 4.12 billion during this period (Mordorintelligence, 2021; Statista, 2022). Despite the prevalence of ITO, satisfaction levels have been suboptimal. Research indicates that about 40% of ITO projects fail (Delenet al., 2019), and failure rates range from 25% to 50% (Luu, 2022). This highlights a significant challenge in achieving satisfactory outcomes in ITO, emphasizing the need to identify factors that can improve success rates.

This study aims to analyze the demographic parameters of ITO from the perspective of service buyers to identify critical success factors for ITO satisfaction in Hong Kong’s FSI. Additionally, it examines the outcomes of ITO based on organization size and staff experience, identifying gaps in the critical success factors affecting satisfaction. The findings will help service providers target their customers more effectively and offer service buyers insights to improve their chances of successful ITO implementation and benefit from its advantages.

Literature Review

ITO involves a diverse range of disciplines that guide various stages of the outsourcing process, incorporating multiple theoretical perspectives addressing various facets of ITO, such as strategy, resources, contracts, relationships, and oversight. A comprehensive overview and empirical investigation conducted in 2020 synthesized the key theories relevant to ITO (Hanafizadeh & Zareravasan, 2020). Common frameworks utilized in ITO research encompass the Technology, Organization, and Environment (TOE) model, Partnership and Alliance Theory, Core Competency Theory (CCT), and Transaction Cost Economics (TCE).

Technology, Organization, and Environment (TOE) Framework

In this conceptual framework, technology encompasses all aspects of business-related technologies, while organization encompasses factors such as management structure, organizational setup, company size, resources, and methods of employee communication. The environmental dimension incorporates market dynamics, competition, and regulatory landscapes (Hanafizadeh & Zare Ravasan, 2018). The TOE framework provides a holistic theoretical approach that considers these three dimensions in understanding adoption, making it adaptable to various theories and models in information systems research. Researchers have the flexibility to customize the elements of each dimension based on the characteristics of the innovation and the organization, ensuring broad applicability across disciplines and contexts (Dewiet al., 2018). The TOE framework finds extensive utility in criteria for success, decision-making processes, and analysis of information security risks (Hanafizadeh & Zareravasan, 2020; Bhattiet al., 2021). While commonly employed to investigate the relationship between ITO adoption, continuous adoption of ITO also reflects satisfaction with ITO. Hence, the Technology, Organization, and Environment (TOE) theory serves as a suitable analytical tool for examining both internal and external factors influencing ITO satisfaction and forms the foundational theoretical framework for this study.

Technology

The term “technology” encompasses all technological assets within the company, including those currently utilized and others that are available but not yet integrated. Furthermore, the company’s existing technological infrastructure plays a significant role in shaping the adaptation process, as it dictates the extent and pace of technological changes that can be implemented (Bhattiet al., 2021).

Perceived Information Security Risk (ISR)

The rapid evolution of technology, including mobile apps, cloud computing, and AI, has significantly enhanced the efficiency of business operations. However, alongside these benefits come IT security vulnerabilities. Companies opting for ITO to capitalize on its advantages must also recognize the accompanying risks (Delenet al., 2019; Al Hadweret al., 2021). Risks represent potential events that could negatively impact a company. For instance, each ITO service provider specializes in distinct areas such as helpdesk services, system management, infrastructure, software development, and cybersecurity. Inadequate expertise from a service provider can result in performance issues or unexpected expenses, posing a threat to the success of the ITO initiative. Another critical risk in ITO revolves around information security. Given the significant importance of perceived IT security risk in the financial services sector, understanding its influence on ITO success is essential (Ahmed, 2020). Hence, establishing the correlation between risk and ITO satisfaction becomes imperative.

Quality of Service Provider (QSP)

The service provider’s quality refers to how well the delivered outcomes align with the expectations of service buyers (Wibisonoet al., 2019). Ramyaet al. (2019) characterize the service provider’s quality as inherent attributes that facilitate effective relational interactions. Wibisonoet al. (2019) discovered a significant impact of service provider’s quality on ITO, corroborating the findings of Al-Azadet al. (2022). However, several other researchers, including. The capabilities of service providers shape their credibility in the eyes of service buyers. Credibility is gauged based on factors such as past performance, skill set, trustworthiness, and integrity (Alwahdani, 2019). Service buyers’ confidence in a service provider directly impacts their decision to continue to use the ITO service.

Organization

The term “organization” encompasses various aspects such as company structure, decision-making procedures, objectives, communication channels, characteristics, and assets of the company. These elements play a significant role in influencing both ITO satisfaction and implementation decisions (Bhattiet al., 2021). It pertains to internal processes or capabilities, which include factors like Contract Management, Internal Contract Experience, and Communication.

Contract Management (CM)

Written contracts are fundamental in overseeing an ITO relationship as they serve various functions (Erdoğan, 2020). Within the realm of ITO, a contract delineates the services to be rendered and their associated costs over a specified contractual period between the involved parties. Once signed, contract management becomes essential (Erdoğan, 2020). Efficient contract management ensures adherence to the stipulated terms and conditions, with each party fulfilling its obligations satisfactorily. Qi and Chau (2015) underscored the significance of contract management quality across both contract and post-contract phases, as it directly impacts ITO. Poor management of contract activities and content by an organization can led to opportunistic behavior and additional costs during service provision, potentially affecting the outcome of the IT project.

Internal Contract Experience (ICE)

Effective administration of preparing the contract stage is vital for managing an ITO relationship. Crafting a thorough contract helps minimize uncertainty, the risk of opportunistic behavior, and misunderstandings between the parties involved (Jain Palvia & Palvia, 2017). It entails preparing the contract’s content, encompassing elements such as pricing, scope of work (SOW), transition procedures, service levels, liabilities, information security and exchange, terms and conditions, penalties, and exit strategies (Gunduz & Elsherbeny, 2020).

The expertise of individuals involved in contract preparation significantly impacts the adequacy and comprehensiveness of the contract in safeguarding the service buyer (Godino & Molina, 2019). Therefore, the contracting experience of involved personnel is crucial in an ITO contract. For example, lacking expertise in contracting may lead to essential tasks being omitted from the drafted SOW. Such omissions can create opportunities for opportunistic behavior and ambiguity, necessitating additional resources to address gaps and potentially resulting in increased service costs. This underscores the importance of involving knowledgeable individuals with contracting expertise in the contract preparation process.

Communication (COM)

Communication involves the processes of understanding, sharing, and generating meaning (University of Minnesota, 2015). It encompasses open dialogues regarding expectations, future trajectories, competencies, strengths, weaknesses, and the consistent exchange of project-related information (Hodosiet al., 2020). Effective communication is essential for knowledge dissemination and nurturing a productive partnership.

In the realm of ITO, communication behavior can be delineated across three dimensions: information exchange, communication quality, and engagement levels (Jatobá,et al., 2022). Communication quality pertains to the accuracy, timeliness, adequacy, and reliability of information (Riedet al., 2022). The success of any prospective collaboration hinges on the execution of effective communication. Partners who excel tend to engage in more frequent and relevant information sharing owing to their deeper relationships (Pai & Yeh, 2015). Effective partnerships are anticipated to exhibit superior communication quality, heightened information exchange between both parties and increased involvement of partners in planning and goal setting.

Environment

The external environment encompasses various factors, including industry structure, regulatory frameworks, and external pressures (Hanafizadeh & Zareravasan, 2020). External pressure can be analyzed from three perspectives: pressure from trading partners, competitors, and regulatory mandates. Regulatory policy constitutes a key aspect of this environmental context.

External pressures and regulatory conditions significantly impact ITO initiatives. Trading partners, market dynamics, regulations, and governmental policies collectively influence the financial services industry (FSI) and may either facilitate or impede ITO endeavors (Hanafizadeh & Zare Ravasan, 2018). Compliance with regulatory requirements is essential for the FSI, as it must adhere to the multitude of regulations set forth by regulatory bodies. The effects of governmental regulations on ITO outcomes can vary, presenting both opportunities and challenges. In instances where governments introduce new regulations affecting the FSI, such as mandating third-party risk management, additional strategies may be necessary to address these regulatory mandates.

Research Methodology

The research model incorporated six independent variables along with demographic variables. It drew upon the theoretical framework of TOE but was tailored to align with the specific context of the financial services industry (FSI) for this study. As for the research methodology, a hybrid approach was adopted, combining both qualitative and quantitative methods. This hybrid method facilitates the validation of research findings by utilizing both quantitative and qualitative data sources, examining quantitative results through qualitative analysis, and informing the development of survey questions (Santoset al., 2017).

The qualitative research approach involves gathering participants’ perspectives and opinions on a specific research subject (Hammarberget al., 2016). To facilitate detailed discussions and enrich data collection, a focus group comprised six individuals either employed in IT roles within the Financial Services Industry (FSI) or provide IT services to the FSI. Participants included individuals with more than 20 years of experience in IT, spanning roles from management personnel to IT professionals and service providers. The diverse backgrounds and expertise of the participants likely yielded valuable insights and varied perspectives on the topic under investigation.

The quantitative research approach systematically collects and analyzes numerical data to describe, predict, or control variables of interest (Rutberg & Bouikidis, 2018). For this study, a survey was administered to gather data from participants employed in the IT sector, particularly those working within or for the Financial Services Industry (FSI) in Hong Kong.

Results

A total of 447 surveys were successfully completed and returned within the designated data collection timeframe, resulting in a response rate of 97%. Relationships were examined through demographic data and statistical analyses, including Independent T-Test and One-way ANOVA. The analysis revealed statistically significant differences between demographic groups and ITO satisfaction within the Financial Services Industry (FSI). The investigation below focuses on demographic data analysis.

Data Demographics

Table I summarizes the demographic of respondents. Among the respondents, 53.9% have FSI experience, and 46.1% have no FSI experience. Around 72% of respondents have ITO experience. The most common respondents have “1–5” times of ITO experiences, representing 43.8% of respondents. On the other hand, “6–10” and “11–20” times of ITO experiences are among 18.3% and 6.5% of respondents, respectively. Over half of the respondents work in accountancy, banking, finance, finance, and computing or IT. 46.3% of respondents are in the IT sector, whereas 16.3% are in accountancy, banking, or finance.

Table I. Demographic of Data

Total number	Respondents (%)
	447	(100%)
FSI working experience
Yes	241	(53.9%)
No	206	(46.1%)
Number of ITO experience
0	124	(27.7%)
1–5	196	(43.8%)
6–10	82	(18.3%)
11–20	29	(6.5%)
21 or above	16	(3.6%)
Current working sector
Accountancy, Banking or Finance	73	(16.3%)
Computing or IT	207	(46.3%)
Healthcare	32	(7.2%)
Marketing	41	(9.2%)
Property or Construction	19	(4.3%)
Retail	10	(2.2%)
Transport or Logistics	7	(1.6%)
Other	58	(13%)
Total number of employees in company in Hong Kong
1–50	154	(34.5%)
51–100	89	(19.9%)
101–250	61	(13.6%)
251–500	50	(11.2%)
501–1000	41	(9.2%)
1001–1500	16	(3.6%)
1501–2500	15	(3.4%)
2501 or above	21	(4.7%)
Total number of employees in the IT department in Hong Kong
1–20	200	(44.7%)
21–50	134	(30.0%)
51–100	51	(11.4%)
101–200	36	(8.1%)
201 or above	26	(5.8%)
Work nature
IT management	102	(22.8%)
IT consultant	72	(16.1%)
IT operation services	82	(18.3%)
IT software development	93	(20.8%)
IT technical services	55	(12.3%)
Non IT professional	43	(9.6%)
Job position
Individual contributor	81	(18.1%)
Supervisor	77	(17.2%)
Manager	98	(21.9%)
Senior manager	60	(13.4%)
Vice president	39	(8.7%)
Management/C-Level	24	(5.4%)
Others	68	(15.2%)
Number of direct and indirect staff
0	110	(24.6%)
1–10	205	(45.9%)
11–20	69	(15.4%)
21–50	42	(9.4%)
51–100	8	(1.8%)
101–200	4	(0.9%)
201–500	5	(1.1%)
501 or above	4	(0.9%)

For the companies the respondents work in, the top 3 ranges of number of employees in Hong Kong are “1–50”, “51–100”, and “101–250”. These three ranges represent 68% of the respondents. 11.7% of respondents’ companies have over 1,000 employees in Hong Kong. For the team size of the IT department, 74.7% have a team under 50 members. 44.7% of respondents have “1–20” IT team members, whereas 30% have “21–50” members. There are also 13.9% of respondents who have over 100 members in the IT department.

The respondents have different consideration in the ITO based on their position. Table II listed the result of cross-tabulation of the most important reason and the respondents’ job positions. From a senior position (senior manager to C-level) perspective, the most important reason is “Transitioning to New Systems or New Technology” at 39.1%. However, “Transfer Business or IT operations Risk” is selected by 64.1% of respondents below senior position (manager to individual contributor). According to the result, the respondents who work at an operational level considered ITO for transferring their risk, whereas the management-level respondents had different considerations. It demonstrates the management-level respondents are more focused on business as usual for considering ITO.

Table II. Cross-Tabulation between ITO’s Most Important Reason and Job Positions

Job position	Cost saving		Improve productivity and efficiency		Transfer business or IT operations risk		Transitioning to new systems or new technology		Others
Individual contributor	23.0%	54.6%	19.8%	63.8%	10.3%	64.1%	12.5%	45.3%	13.3%	53.3%
Supervisor	15.5%		21.6%		19.2%		10.9%		20.0%
Manager	16.1%		22.4%		34.6%		21.9%		20.0%
Senior manager	12.1%	24.7%	11.2%	23.3%	16.7%	29.5%	18.8%	39.1%	6.7%	33.3%
Vice president	6.9%		9.5%		9.0%		10.9%		13.3%
Management/C-Level	5.7%		2.6%		3.8%		9.4%		13.3%
Others	20.7%	20.7%	12.9%	12.9%	6.4%	6.4%	15.6%	15.6%	13.3%	13.3%

Independent t-Test Analysis

The independent sample t-test was utilized to ascertain whether there were variations in IT outsourcing satisfaction based on experience in the Financial Services Industry (FSI). If the p-value is below 0.05, the group means are considered statistically significant (Jafari & Ansari-Pour, 2019). In this scenario, “IT outsourcing satisfaction” serves as the dependent variable, while “FSI experience” acts as the independent variable, with two distinct groups: “FSI” and “non-FSI”. The results of the test are presented in tabular format in Table III. Notably, the significance (Sig.) value of Levene’s Test exceeds 0.05, indicating that the null hypothesis is not rejected. The data on row “Equal variances assumed” should thus be read. In the “Significance” column of the table, the p-value of one-sided is lower than 0.05. It represents that the group means are statistically significantly different. Hence, the respondents who had FSI experience have higher IT outsourcing satisfaction (ITOS) levels than the respondents who have non-FSI experience, and the summary of t-test result is shown in Table IV.

Table III. Independent T-Test Result

		Levene’s test for equality of variances
		F	Sig.	t	df	Significance
						One-sided p	Two-sided p
ITOS1	Equal variances assumed	0.498	0.481	1.695	445	0.045	0.091
	Equal variances not assumed			1.695	434.39	0.045	0.091
ITOS2	Equal variances assumed	2.426	0.12	2.216	445	0.014	0.027
	Equal variances not assumed			2.231	442.636	0.013	0.026
ITOS3	Equal variances assumed	0.522	0.47	3.924	445	<0.001	<0.001
	Equal variances not assumed			3.935	438.415	<0.001	<0.001
ITOS4	Equal variances assumed	0.001	0.98	3.638	445	<0.001	<0.001
	Equal variances not assumed			3.641	435.765	<0.001	<0.001

Table IV. Summary of Independent T-Test Result

	FSI experience	Mean	Std. deviation	Significance one-sided p
ITOS1	Yes	4.46	1.049	0.045
	No	4.30	1.047
ITOS2	Yes	4.48	1.133	0.014
	No	4.25	1.042
ITOS3	Yes	4.60	1.032	<0.001
	No	4.22	0.997
ITOS4	Yes	4.71	0.990	<0.001
	No	4.37	0.978

One-way ANOVA Analysis

One-way ANOVA determines any statistically significant difference in the groups of independent variable and dependent variable.

ITO Reason

For the ITO reason of the organization, the top 3 reasons of ITO were 38.9% of cost saving, 26% of Improve Productivity and Efficiency, and 17.4% of Transfer Business or IT Operations Risk. The analysis determined a statistically significant difference in ITO satisfaction between “Costing Saving” and “Transitioning to New System or New Technology,” and the result is shown in Table V. The ITO satisfaction of “Transitioning to New System or New Technology” was statically significantly higher than “Costing Saving,” which was presented by mean plots in Fig. 1. “Costing Saving” is the top one reason for ITO, but the ITO satisfaction is lower than “Transitioning to New System or New Technology,” which is second last in the ranking. It probably has unexpected costs during ITO that failed to meet the objective of cost saving. “Transitioning to New System or New Technology” is higher satisfaction in ITO, which implies the organization avoids the risks and uncertainties in system transition. They are willing to outsource it to external parties.

Table V. One Way ANOVA Result of ITO Reason

Descriptives
ITO reason	% of respondents	Mean	Std. deviation
Cost saving	38.9%	4.440	1.067
Improve productivity and efficiency	26.0%	4.600	0.941
Transfer business or IT operations risk	17.4%	4.590	1.012
Transitioning to new system or new technology	14.3%	4.800	0.876
Other	3.4%	4.330	0.900
Multiple comparisons
ITOreason (I)	ITOreason (J)	Mean difference (I-J)	p
Transitioning to new system or new technology	Cost saving	0.436*	0.049

Fig. 1. Means plots of ITO reason.

Number of ITO

The analysis examines the correlation between IT outsourcing (ITO) experience and satisfaction. ITO experience plays a pivotal role in facilitating ITO success, and the results of the analysis are presented in Table VI. With a p-value below 0.05, the analysis indicates a statistically significant difference between the groups concerning the number of ITOs. In the Multiple Comparisons table, further information was provided to understand which group differed. There was a statistically significant difference in ITOS between “11–20” and “1–5” that p-value was less than 0.05, which was present in Fig. 2. It concluded that the ITOS was statistically significantly higher for respondents in the group “11–20” compared to “1–5.” The ITO experience helps the staff determine the scope of work and defense in ITO, preventing opportunism. Ultimately, the service buyer satisfies the ITO service easily.

Table VI. One Way ANOVA Result of ITO Experience

Descriptives
No. of ITO	Mean	Standard deviation
0	4.250	0.968
1–5	4.570	0.950
6–10	4.710	1.149
11–20	5.210	0.675
21 or above	4.880	0.619
Multiple comparisons
No. of ITO (I)	No. of ITO (J)	Mean difference (I-J)	p
11–20	1–5	0.641*	0.009

Fig. 2. Means plots of number of ITO.

Number of Staff

The analysis results determined groups “1–50,” “51–100,” and “251–500” have a statistically significant difference in Table VII. Compare the mean value between these three groups. It demonstrated the ITO satisfaction of groups “51–100” and “251–500” is higher than group “1–50” in Fig. 3. It is probable that the companies of this range of staff, which ITO is uncomplicated, have a specific legal and procurement team to govern the business contract.

Table VII. One Way ANOVA Result of Number of Staff

Descriptives
No. of staff	Mean	Standard deviation
1–50	4.140	0.966
51–100	4.610	0.961
101–250	4.560	0.992
251–500	4.660	0.917
501–1000	4.540	1.286
1001–1500	4.560	1.094
1501–2500	4.730	1.163
2501 or above	4.290	1.146
Multiple comparisons
No. of staff (I)	No. of staff (J)	Mean difference (I-J)	p
51–100	1–50	0.464*	0.015
251–500	1–50	0.517*	0.040

Fig. 3. Means plots of number of staff.

Job Position

For a job position of respondents, the result demonstrated the statistical significance between three positions, which are “Individual Contributor,” “Supervisor,” and “Senior Manager.” Table VIII shows the analysis result that the “supervisor” and “senior manager” have statically significantly higher than “Individual Contributor.” ITOS 2 is satisfaction that ITO transferred the risks, and ITOS 3 is satisfaction with the benefits from ITO. “Individual Contributor” probably focuses on operations in their daily duties. Risks and other benefits are not considered in their position. The mean values of ITOS 2 and 3 are shown in Figs. 4 and 5.

Table VIII. One Way ANOVA Result of Job Position

Descriptives
	ITOS 2		ITOS 3
Job position	Mean	Standard deviation	Mean	Standard deviation
Individual contributor	4.420	1.150	4.420	1.150
Supervisor	4.650	1.061	4.650	1.061
Manager	4.540	0.910	4.540	0.910
Senior manager	4.880	0.922	4.880	0.922
Vice president	4.640	0.873	4.640	0.873
Management/C-Level	4.580	1.139	4.580	1.139
Others	4.340	0.891	4.340	0.891
Multiple comparisons
	Job position (I)	Job position (J)	Meandifference(I-J)	p
ITOS 2	Senior manager	Individual contributor	0.614*	0.017
ITOS 3	Supervisor	Individual contributor	0.512*	0.029

Fig. 4. Means plots of ITOS 2.

Fig. 5. Means plots of ITOS 3.

Multiple Regression Analysis

Multiple regression analysis can determine the relationship between a single dependent variable and two or more independent variables (Plonsky & Ghanbar, 2018). The formula for multiple regression:

(1) $$\begin{array}{r}Y=B_0+B_1{X}_1+B_2{X}_2+\cdots +B_n{X}_n\end{array}$$

where X₁, X₂, …, X_n are the n independent variables (Plonsky & Ghanbar, 2018).

The multiple linear regression test must be carried out to consider the multiple factors involved, as the research model in this study should be viewed as a whole. The independent variable (ITOS) was predicted as the value based on six independent variables (ISR, QSP, CM, ICE, COM, and RP). Finally, two factors (ISR and CM) were removed due to Sig. > 0.05 during the analysis process, and only QSP, ICE, COM, and RP factors were significant independent variables. Table IX–XI displayed the results of multiple linear regression.

Table IX. Summary of Multiple Regression Analysis

Model summaryb
Model	R	R square
1	0.854a	0.730

Table X. ANOVA of Multiple Regression Analysis

ANOVAa
	F	Sig.
Regression	298.248	<0.001b

Table XI. Coefficients of Multiple Regression Analysis

Coefficientsa
Model	Unstandardized coefficients (B)	Sig.
(Constant)	0.224	0.073
Average of QSP	0.337	<0.001
Average of RP	0.193	<0.001
Average of COM	0.089	0.047
Average of ICE	0.332	<0.001

The 0.854 R-value (multiple correlation coefficient) was a very strong correlation. The R square (R²) was 0.730, which implied that 73% of data variation could be explained by this model, which was a very large amount. The group of independent variables reliably predicted the ITOS because the Sig. (p) value in the ANOVA was less than 0.05. It meant that the variables were generally numerically substantially predicted by the regression model. The Sig. (p) values of the four independent variables were less than 0.05 in the Coefficients. The QSP, ICE, COM, and RP contributed statistically significantly to the model. Unstandardized Coefficients were the values of increment in ITOS for a 1-unit change in the corresponding independent variables. After the multiple regression test was conducted, the values were substituted to equation (1), and the final formula was shown below:

$$\begin{array}{rl}Y& =0.224+0.337\times QSP+0.332\times ICE+0.089\\ & \times COM+0.193\times RP\end{array}$$

Conclusion and Recommendations

Conclusion

The result determined the satisfaction of ITO by different demographic groups. It determined the statistically significant differences in ITO satisfaction between the groups: ITO reason, ITO experience, number of staff, and respondent’s job position. It also provided insights to service providers for approaching their target customers in the market:

1. The above analysis demonstrated that small and midsize enterprises (SMEs) are the majority (54.4%) of businesses that use ITO services. 34.5% of “1–50” and 19.9% of “51–100” employees, but the satisfaction rate of the group “51–100” is higher than group “1–50.”

2. 38.9% of organizations used ITO services to save money, but there is no significant satisfaction compared with 14.3% of system or technology transition.

Recommendations

The result demonstrated that SMEs have a high demand for ITO services in their business. Improving the satisfaction rate of the above findings can enhance the intention to use ITO services continuously. Moreover, service providers can adjust their business strategy to attract new customers to SMB organizations. There are recommendations below to facilitate the SME’s use of ITO services and increase satisfaction.

Clearly Define Objectives

Service providers should communicate with service buyers in-depth to understand their objectives and expectations. It is good practice to consider both short-term and long-term goals. Service providers clearly articulate how the services align with customer needs. For example, the goals are cost savings, improving service quality, risk reduction, and transitioning to a new system or technology. Working with customers to define specific and measurable outcomes that the outsourcing aims to achieve. For example, response time and resolution rates.

Define Scope and Deliverables

It is an important step in ITO and often has arguments between service buyer and provider. The service providers should pay more attention to this section to define the scope and deliverables, which are crucial for setting clear expectations and ensuring successful delivery.

• Scope Definition: Provide a detailed description of the work to be outsourced, including specific tasks, activities, and deliverables. This description should be comprehensive enough to leave no room for ambiguity or misinterpretation. Detail outline what is included in the scope of work and, equally importantly, what is not included. This helps prevent scope creep and ensures that both the SME and the service provider are on the same page regarding project boundaries. Identify any constraints or assumptions that may impact the scope of work. For example, budgetary constraints and resource limitations. Clearly define the roles and responsibilities of both the SME and the service provider. This includes identifying key stakeholders, team members, and other individuals involved in the ITO.

• Deliverables: Service providers produce specific tangible outputs or deliverables. These deliverables should be clearly defined, measurable, and aligned with the ITO’s objectives. Examples of deliverables could include software applications, reports, documentation, or other artifacts. Establish clear quality standards and acceptance criteria for each deliverable. This ensures that the deliverables meet the desired level of quality and functionality. Quality standards may include factors such as performance, reliability, security, and user experience.

Besides clearly defining the scope, extra professional man-days should be included in the ITO service. This is because service buyers may not clearly know the scope of IT outsourcing. Some tasks or activities may not be included in the scope, causing extra costs in ITO. The cost-saving objective may fail if it is the goal of the ITO. Professional man-days are a way to handle this uncertain situation. They reduce the failure of the goal and the arguments of responsibilities that are not defined in scope.

Service Performance Monitoring

To ensure ongoing service quality and mitigate the risk of failure, service providers should regularly track their performance. Performance monitoring involves measuring and assessing their performance regularly. This monitoring process helps identify potential performance issues and allows timely intervention and remediation. By tracking performance trends over time, service providers can determine if performance is trending towards breaching pre-defined SLA alert thresholds, indicating a potential performance issue. When a service provider identifies a performance issue, they can proactively allocate resources to resolve it. It’s essential to monitor key aspects such as cost, response time, time taken to solve problems, and the rate of on-time delivery throughout the service’s duration. Keeping track of these indicators enables service providers to understand and fulfill the agreed service levels efficiently and ensure timely and effective service delivery.

Performance review sessions allow both parties to share information, address any issues that may arise in daily operations, and work together to find solutions. These sessions facilitate ongoing communication and collaboration between service buyers and service providers, further enhancing the quality of the outsourcing relationship.

Limitation and Future Research

This research methodology encountered certain limitations that could have impacted the outcomes.

Limitations

The utilization of the snowball sampling method could potentially introduce biased data due to its inherent characteristics. For example, individuals within the snowball structure may consist predominantly of current or former colleagues who likely share similar experiences or outcomes related to ITO. Consequently, the representation of these samples may skew towards a particular demographic group and may not accurately reflect the entire industry population. Employing stratified sampling, which involves categorizing FSI companies into subgroups and selecting samples from each subgroup, could offer a more representative approach.

In future research endeavors, a broader research scope would be necessary to comprehensively understand the entire population, thus providing industry stakeholders with more pertinent insights to inform policy development.

This study did not delve into the scale of ITO or the causes of ITO failure. Exploring the correlation between critical success factors and the reasons for ITO failure could yield intriguing insights for future research.

Future Research

The demographic analysis identified the cross-tabulation between ITO’s most important reason and job positions in Table IV but cannot determine the association in chi-square analysis. The extensive sampling size may require analysis in further research.

Future research endeavors will center on exploring the scale of IT outsourcing (ITO), the awareness of critical success factors among service buyers, and potential gaps in understanding regarding failure causes. Investigations may delve into whether service buyers are uninformed about failure causes or aware but fail to take remedial action in ITO scenarios. Such inquiries aim to enhance satisfaction rates in IT outsourcing.

Conflict of Interest

All authors declare that they have no conflicts of interest.