1. Introduction
Public complaints about government services in Indonesia have been well reported in mass media. Civil claims cover many government services such as public health services, ID applications, driver’s license applications, and birth and death certificates. Government services in public sectors are perceived to be slow and corrupt. The public sector integrity survey in 2021 conducted by the Corruption Eradication Commission of Indonesia identified that around 30 percent of ministries, agencies, and district governments are still prone to corrupt practices (Saroh & Ferdinan, 2021). Studies indicate that the corruption rate relates to inefficiency and quality public services (Phan & Nguyen, 2020).
Gronroos (2019) stated that most public service organizations are not efficient since they do not apply a service-oriented approach to serving citizens. Governmental cost-cutting initiatives and growing public pressure have led to the need to improve public services’ efficiency and effectiveness continuously. According to Torfing et al. (2016), the government has a huge challenge to transform the bureaucratic public service image into a public service image providing a collaborative creation of services.
One of the critical success factors for a company in a demanding business environment is providing service orientation (Gronroos, 2019; Lytle et al., 1998). Companies are often trying to create their image by managing the types of behavior performed by employees (Jung & Yoon, 2013; Popli & Rizvi, 2015). In other words, a service-oriented organization is encouraged to be productive, efficient, and humanistic. The organization can provide communicative and interactive quality service between front liners and customers. Therefore, employees play a significant role since employee attitude and behavior greatly influence consumer perceptions of company service quality (Popli & Rizvi, 2015).
Construct for service orientation has been tested by marketing scholars in various service settings, such as in restaurants (Kim, 2011; Yen et al., 2016), hotels (Jung & Yoon, 2013), banking (Frimpong & Wilson, 2012; Tung et al., 2014), airline (Nair et al., 2013), and telecommunication (Luk et al., 2013). While most previous studies of service orientation were conducted in western cultures where the economy is relatively well established, the same studies for emerging economies are relatively rare (Luk et al., 2013). Saura et al. (2005) even suggested that cross-cultural approaches to the construct of service orientation analyzed would be interesting to check for differences in conceptualization and operationalization. It is also essential to examine how the service orientation is implemented in the public sector since empirical evidence is relatively limited (Akesson et al., 2008; Caemmerer & Wilson, 2011). In the public sector context, especially in developing economies like Indonesia, research on service orientation is relatively rare. Therefore, it is the intention of the study to establish service orientation constructs relevant to the public sector and examine the relationship between service orientation and public sector performances.
The study will contribute to the body of knowledge by providing a construct measurement tailored to the public sector setting, reflecting policy and practice that create and support employee attitude and behavior to deliver quality services to public sector customers. Although the approach and exercise may not easily be implemented since it could be against stakeholder agendas or interests (Lin et al., 2018), created resistance among employees, or management was concerned more with politics than public interest (Gronroos, 2019), a strong public demand for more transparent, accountable, and quick public services has become a priority in the millennium era. This study could also fill the research gap since previous studies testing the validity and reliability of the construct in the public sector are relatively rare. Indeed, the construct has a complex and multidimensional structure (Frimpong & Wilson, 2012). The different settings of in-service orientation would result in other implications for organizations. It is, therefore, the intention of the study to fill the theoretical gap so that the construction would have a more comprehensive perspective.
2. Literature Review and Hypotheses
2.1. Service Orientation
Marketing scholars and practitioners have not reached a collective agreement about the definition of service orientation. Frimpong and Wilson (2012) stated that the concept of service orientation is perceived as a vogue terminology due to its various interpretations of the multi dimensions of the construct. Lytle et al. (1998, p. 459) defined an organizational service orientation as “an organization-wide embracement of a basic set of relatively enduring organizational policies, practices, and procedures intended to support and reward service-giving behaviors that create and deliver service excellence.”
A different opinion was proposed by Hogan et al. (1984, p. 167), who perceived service orientation based on a personality trait perspective, namely as a disposition to be helpful, thoughtful, considerate, and cooperative. In this case, service orientation is a set of employee attitudes and behavior that influence the quality of interaction between employees and customers. Johnson (1996, p.838) defines “service orientation in delivery as the extent to which branch employees solve customer problems, cooperate to solve customer problems, are committed to providing excellent service, and feel a personal responsibility for their work.”
In its development, the definition of service orientation had been perceived from business strategy (Homburg et al., 2002; Lee et al., 1999), business model innovation (Nair et al., 2013), and e-service setting (Rust & Kannan, 2013). Researchers have revealed the role of service orientation in boosting company performance, employees, and customers. Some studies showed the relationship of service orientation with trust in the organization and confidence in management (Caemmerer & Wilson, 2011), service quality image and commitment (Lytle & Timmerman, 2006), employee engagement (Popli & Rizvi, 2015), customer loyalty (Tung et al., 2014), and business performance (Homburg et al., 2002).
Service orientation was also measured based on individual perspectives, such as personality traits introduced by Hogan et al. (1984), who developed the Service Orientation Index (SOI) scale. SOI scale consists of 92 items grouped in four dimensions: agreeableness, adjustment, conscientiousness, and sociability. In addition to personality traits, service orientation at the individual level can also be seen from the service delivery perspective (Frimpong & Wilson, 2012; Yen et al., 2016). The work of Yen et al. (2016) confirmed service orientation dimensions tested by Kim (2011), which consisted of organizational support, customer focus, and service under pressure.
In addition to the individual level of performance, service orientation can also be seen from an organizational perspective level or better known as a macro-organizational approach (Homburg et al., 2002). At the executive level, service orientation can be perceived as corporate culture/ climate (Luk et al., 2013; Lytle et al., 1998) and business strategy (Homburg et al., 2002; Tung et al., 2014). The work of Lytle et al. (1998) has become the primary source of reference for developing a construct of organization service orientation. They offered a construct of organizational service orientation consisting of 36 indicators grouped into 10 ten sub-dimensions. Each sub-dimension is categorized within one of the four broad areas of service-related practices theorized to be linked with service performance: service leadership practices, customer contact practices, human resource management practices, and service system practices. Akesson (2008) has refined the work of Lytle et al. (1998) by offering the fifth dimension, service design.
2.2. Organizational Performance
It is interesting to note that both academics do not have a joint agreement on the definition of performance. Scholars have a deal that performance is a multidimensional construct that can be viewed from different perspectives. From a process perspective, performance is the transformation of input into output. From an economic standpoint, performance is the relationship between effective cost, realized output, and achieved outcome (Jarad et al., 2010). On the other hand, Choi and Moon (2017) perceived that performance is behavior and should be differentiated from outcome since the outcome can be contaminated by a factor beyond the control of the performer. The debate on the construct of performance, whether it is behavior, result, or both, is a challenge for managers of public sector organizations to examine and manage performance comprehensively.
Performance is not only categorized as being financial (monetary) (Lee & Manorungrueangrat, 2019) but also as non-financial (non-monetary), such as customer and employee associated (Dimitropoulos et al., 2017; Soelton et al., 2021). Verbeeten (2008) revealed that public sector organizations have to consider a tradeoff between quantitative goals (for example, short-term performances such as efficiency and quantity produced) and quality goals (for instance, long-term or strategic performance goals such as quality, innovation, and employee morale).
Since the characteristics of public sector organizations are different from those of private sectors, public sector managers are challenged to develop a more relevant performance measurement (Peng et al., 2007). Practically, measuring public sector performances is difficult due to some issues. First, it is more difficult to examine which indicators in public sectors are relevant to measure performance since the problem is more conceptual than technical (van de Walle, 2008). For instance, what is the role of the public sector, and what is an excellent performance? Second, non-financial returns or qualitative versions such as public image and perceived service quality (Jarad et al., 2010; Moideenkutty et al., 2011) commonly applied in measuring public sector performances are subjective. Subjectivity in public sector performance measurement is also due to the data collection methods and data measurement. Most data employed in the public sector measurement are society perceptions of public sector service performances directly collected from respondents in a given time.
According to Carter et al. (1992), qualitative performance is perceived as “operational quality.” Organizational service quality, a part of the corporate operation, is measured based on consumer experiences of the quality of the public sector services provided during the evaluation process. Experiences felt by customers indeed create their perception and behavior. A positive attitude would undoubtedly lead to loyalty, and a negative perception would probably lead to complaints. Osborne (2017) described the relationship between frontline employees and service users in the public sector differs significantly from the business sector. In the private sector, getting a customer to return is essential, while in the public sector, a returning customer could be a sign of a service failure.
A complaint in the public sector is a way of communication from citizens dealing with an unfairly suffered discomfort, sometimes as a consequence of service not or only partly provided (Minelli & Ruffini, 2018, p.48). Besides, qualitative performance is also perceived as “strategic capacity” related to innovation and long-term effectiveness (Kaplan, 2001). Indeed, innovation is a determining factor of company growth in the future.
2.3. Hypotheses
In the public sector context, successful front-line interactions between citizens and public bureaucrats, such as handling information requests, processing license applica- tions, or assessing benefit claims, are a significant determinant of overall service performance (Brewer, 2007). Organizational service performance can also be seen from corporate and individual perspectives (Lytle & Timmerman, 2006; Soelton et al., 2021). According to Moideenkutty et al. (2011), public sector performance was influenced by employee behavior, and their behavior became a source of sustainable competitive advantage for an organization. Thus, the frontline response would be critical in influencing citizen perceptions of public sector performances. It should be noted; however, employee behavior is not formed in the short term. Lee et al. (1999) pointed out that it is the result of a lifetime corporate culture. It can be concluded that service orientation enhances organizational performance (Jung & Yoon, 2013; Tung et al., 2014; Yen et al., 2016).
Since quantitative measurement in the public sector is difficult to apply and less critical (Duque-Zuluaga & Schneider, 2008), the study employs qualitative performances. Previous studies have used different constructs to assess organizational performances. Lytle and Timmerman (2006) and Rho et al. (2015) stated that service quality image is a significant predictor of corporate achievements. Lee et al. (1999) revealed that service orientation determined service quality image and organizational growth. Kowalkowski et al. (2013) argued that IT effectiveness was the catalyst for organizational service orientation. Bifulco et al. (2016) and Hackler and Saxton (2007) stated that the effectiveness of ICT usage was crucial in providing superior services. Another critical performance indicator is the innovation of the organization. Innovation in the public sector is usually based on the need of the government to respond to the public expectation of better service. The relationship between service orientation and innovation was explained by Nair et al. (2013). According to Hutapea et al. (2021), innovation creates an organizational climate that generates successful innovative activities. Further, Akhtar et al. (2021) argued that empowerment is an essential component influencing service innovation. Organizational performance measurement can also be seen in the public complaint (Brewer, 2007; Rebora et al., 2016). Complaints can be considered a guideline for a public service organization to understand the needs and expectations of citizens related to added-value services (Simmons & Brennan, 2017). Brewer (2007) elucidated that the level of organizational service orientation was reflected by how far the organization deals with the complaint intensity of the public services.
Having reviewed empirical evidence from various previous studies, the study will examine the relationship between service orientation and other organizational performance attributes specified for the context of the public sector setting, including organizational growth, service quality image (corporate image), IT effectiveness, service (organizational) innovation, and public complaint. The study, therefore, hypothesizes that:
H1: Service orientation is significantly and positively related to organizational growth.
H2: Service orientation is significantly and positively related to service quality image.
H3: Service orientation is significantly and positively related to IT effectiveness.
H4: Service orientation is significantly and positively related to service innovation.
H5: Service orientation is significantly and negatively related to a public complaint.
3. Research Methods and Materials
3.1. Research Design
The population target in the study is front-liners that serve citizens or public sector customers in the service encounter process. The data was obtained from service frontline employees in the public sector in the Bengkulu province of Indonesia. Employees of the government organizations serving citizens in the police stations, hospitals, district offices, department of population and civil registration, income and asset management office, and tax service office were targeted for the survey. Six hundred questionnaires were distributed, and four hundred and eighty-eight were returned and analyzed.
The study was conducted in two steps. The first step was a purification of the items of the SERV*OR Scale developed by Lytle et al. (1998) tailored for the public sector setting. Since two items of the 36 original items of the SERV*OR scale are not relevant in the public sector context, the researchers apply 34 items for the study. A list of the items employed for the study is depicted in Table 1. Thomas et al. (2001) supported the reduction of the items used. “It would be useful to examine if the scale’s number of items could be lowered while retaining the scale’s dimensionality and consistency, ” they said. Before the survey, the researchers conducted a pretest involving experts of both managers of nonprofit organizations and survey experts. It was undertaken to ensure that respondents would easily understand the questionnaire.
Table 1: Measurement Item of Service Orientation
The second step tested hypotheses between service orientation variable and organizational growth, service/ corporate image, IT effectiveness, service/organizational innovation, and public complaint. As there is also no consensus in the literature on conceptualizing and measuring service (organizational) performance (Gronroos, 1990), subjective measurements are also tolerated. Several authors prefer to employ subjective performance measures due to the multidimensional nature of the construct (Venkatraman & Ramanujam, 1987). Self-reporting perceived steps are acceptable when an objective standard is unavailable (Vandenabeele, 2009). In this study, the organizational performance measurement is employee subjective evaluation of the organizational performance in the last three years. The validity and reliability of the items were examined. All validity and reliability checks provide satisfactory results. Factor analysis and regression analysis were employed in the dataset.
4. Results and Discussion
4.1. Factor Analysis of Service Orientation
The researchers were interested to see whether respondent perceptions of service orientation of public sector organizations could be grouped into a smaller number of underlying factors. Factor analysis was employed in the dataset of the 34 service orientation indicators. The principal component analysis was applied to the dataset to extract (from the series of 34 service orientation indicators) a set of factors capable of capturing the main features of responses. Before extracting factors, Bartlett’s Test of Sphericity (0.00) and the KMO (.92) measure of sampling adequacy confirmed sufficient correlation among the variables to employ factor analysis. To simplify the factor pattern, a Varimax rotation was conducted.
The next step in a factor analysis was to determine the number of factors to extract from the dataset. It was decided to follow the convention in selecting factors that account for variances (eigenvalue) greater than one. Factors with a variance of less than one are no better than a single variable since each variable has a variance of one (Hair et al., 2013). The eigenvalues are displayed in the penultimate row of Table 2. The eigenvalue suggests a five-factor solution. The last row of Table 2 shows the percentage of variance in the complete set of the 34 service orientation variables attributed to the five factors. The cumulative value of total variance explained by the five-factor solution was 61.94%. Thus, a model with five factors was considered adequate to represent the data. The significant correlations between factors and state variables are displayed in Table 2. A cut-off value of .50 was applied. The cut-off value of .50 was deemed sufficient since the survey’s sample size is more than 300 (Hair et al., 2013).
Table 2: Validity Test Result Based on Fit Model’s Loading Factors
The following interpretations are offered in light of the factor loadings depicted in Table 2.
Factor 1: Technology, Information, and Communication. This factor exhibits the largest number of significant correlation coefficients. Factor 1 has heavy loadings for eight variables, mainly relating to standard of services technology performed by the public organizations and service standard communication commonly used and regularly communicated to employees in the public departments. Three of the eight variables in the factor reflect service technology in the public sector related to service capability through technology, the technology used to develop higher levels of service quality, and technology supporting the effort of frontline employees. Four variables in this factor reflect service standard communication commonly used in the public sector, and the rest of the variables reflect the organization’s efforts to treat customers. This study suggests that the public department needs to increase the use of ICT in improving public services.
Factor 2: Service Vision. Factor 2 has heavy loadings for six variables pertaining to the service vision of the public organization. Customer treatments that correlate with this factor are employee concern for the customers and comparative advantage over the competitor. Therefore, the factor was named accordingly.
Factor 3: Service Delivery. Factor 3 comprises seven variables that reflect service failure recovery and service standard communication. Service failure recoveries that have a high correlation with this factor are related to the effort of the public organization in providing exemplary service to customers. This factor is then named service delivery.
Factor 4: Service Training and Empowering. Factor 4 has heavy loadings on five variables that reflect employee empowerment and service failure prevention. Three of the five variables reflect employee empowerment in the public sector. Employee empowerment is vital for the public organization to improve the quality of public services. Empowering employees appropriately can enable employees to provide superior service and reduce customer inconvenience. The factor has thus been labeled service training and empowering.
Factor 5: Servant Leadership. The factor has been named accordingly since the three variables were related to the leadership role in emphasizing the importance of service management. Three variables that make up this dimension include constantly measuring service quality, management caring about service, and providing a resource to provide excellent service. Therefore, the factor is labeled “Servant Leadership.”
Having conducted a factor analysis on the dataset, it is crucial to examine the reliability of the construct of service orientation developed for the public sector organizations. Table 3 exhibits the reliability test results for each dimension of service orientation developed. The cut-off coefficient of Cronbach alpha 0.70 is used as a threshold (Hair et al., 2013). The results of the reliability tests indicate that the scale developed is consistent.
Table 3: Reliability Test of the Dimensions of Service Orientation
4.2. Hypothesis Testing
Regression analysis was conducted to examine the relationship between independent variables (factor scores of the dimensions of service orientation) and dependent variables (organizational growth, service quality image, technology image, service innovation, and complaint intensity). The regression analysis results indicate that service orientation indeed influences organization performances. All five organizational performance measures employed as dependent variables are significantly influenced by service orientation. The results of the hypothesis testing are shown in Table 4.
Table 4: Hypothesis Test Results
Note: SO: Service Orientation; OG: Organizational Growth; SQI: Service Quality Image; ITE: Information Technology Effectiveness; SI: Service Innovation; PC: Public Complaint. ***p-value < 0.001, **p-value < 0.05.
5. Conclusion
The study results identify those dimensions of service orientation constructs are different from the ones commonly applied in the business sector. The study proposes five dimensions of service orientation tailored to the need of the public sector organizations, namely factor 1 (technology, information, and communication), factor 2 (service vision), factor 3 (service delivery), factor 4 (service training and empowering), and factor 5 (servant leadership). The study results also reveal that service orientation dimensions positively influence public sector organization performances (organization growth, service quality image/corporate image, IT effectiveness, service/organizational innovation, and civil complaint intensity).
It is interesting to note that ICT contributes significantly to informing the dimensions of service orientation for public sector organizations. It seems transparent that public sector organizations cannot ignore the impact of the speedy growth of ICT in public sector services. It is also imperative that respondents perceive service vision as the essential dimension in creating the service orientation scale. The lack of clear direction in planning and implementing (service vision) in public sector organizations could be one of the reasons why the public sector is far behind the business sectors in designing service culture. The model developed also identifies that service delivery design, training and empowering, and servant leadership form significant factors in the construction of service orientation for public sector organizations.
Thus, for public sectors to improve their services, they need to design a service orientation strategy focusing on the five factors identified in the study since these five dimensions of service orientation significantly and positively influence organizational performances. Investing in IT to support the service system would undoubtedly enhance the quality of public sector services. It is also important for government organizations to provide clear guidance to improve their service vision since delivering quality services is a relatively new culture in government offices. Redesigning the service delivery system could also improve the speed of services in the public sector. Employee training and empowerment is another issue that needs to be addressed by the government to avoid service failures in the first place and to match the quality services of the private sector. Government employees should be prepared adequately to match new challenges in public sector services due to significant environmental changes such as technology and globalization. Finally, to improve servant leadership, the management of public sector services needs to show and demonstrate a high commitment to providing excellent services.
Although the study has been able to identify the dimensions of service orientation for public sectors, the model developed should be further tested since the types of public areas studied are limited to various kinds of public sector organizations. While the result of the study might be appealing in an attempt to understand service orientation in the public sectors, further investigation of the prerequisites of implementing service culture and service orientation should be conducted.
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