Port service quality assessment using a ROPMIS modeling: seaports scenario in a Gulf country

2.1 Service quality perspectives of Omani ports

Omani ports had assistance from their logistics networks to connect with 86 ports in 40 countries (US International Trade Administration, 2021). The logistics performance index (LPI) ranked Oman 43rd out of 160 countries worldwide with a score of 3.20 out of 5 (The World Bank, 2018). Compared to the logistics performance study of 2016, Oman improved slightly in logistics performance by ranking 48th in the biennial report. The highest mean rating was given to the “timeliness” indicator, which received a score of 3.80, while the “customs” indicator received the lowest mean rating of 2.76, indicating a need to improve customs and border management clearance to expedite the release of cargoes from the customs office (The World Bank, 2018).

The supply chain and procedures underwent significant changes due to continuous progress, and technological and industrial revolutions and these changes resulted in a wide-scale domino effect. The shortage of qualified logistics personnel posed a severe threat to the country's economic progress, creating acute suffering (Benayoune, 2018), particularly for ports, which derived demand facilities (OECD, 2008).

Port operations have become a focus of discussion and research among expert groups and individuals, primarily due to their potential in a competitive trade area. Nguyen et al. (2022) emphasized that the enhancement of PSQ is considered the primary benchmark of a nation's competitive capacity, which was also supported by Schøyen et al. (2018). Without excellent service quality provided at a port, port users may choose other ports and terminals, thereby impacting the business efficiency of port operating companies (Nguyen et al., 2022).

However, as no previous service quality research had been conducted on Omani ports, this study aimed to evaluate the service quality of the three major Omani seaports mentioned using the most comprehensive PSQ measurement model.

2.2 Systematic literature review of port service quality (PSQ) measurement models

The quality of ports in a country can be evaluated in various ways, as seen in the studies conducted by Yeo et al. (2015), Thai (2016), Limbourg et al. (2016) and Onyemechi et al. (2017). Yeo et al. (2015) found a direct link between PSQ and customer satisfaction, while Thai (2016) and Yeo et al. (2015) contributed to the actual management practices within ports by constructing a reliable PSQ scale to measure customer satisfaction. Limbourg et al. (2016) used the five dimensions of the Service Quality (SERVQUAL) model to measure PSQ and identified the importance of logistics service providers (LSPs) in delivering commendable services. Meanwhile, Onyemechi et al. (2017) reported positive changes in port services following the transfer of terminal operations from public to private terminal operators, which introduced competition and forced operators to provide quality services to attract and retain customers. Private investments in constructing new facilities have also resulted in positive outcomes regarding SERVQUAL dimensions.

Although various industries have been studied extensively to measure service quality, the research on this topic in the maritime industry, particularly in ports, has been limited. Most maritime-related literature concentrates on carrier and port selection rather than the thorough measurement of service quality in this sector (Thai, 2016). According to Phan et al. (2021), research on service quality in the maritime sector and ports has not been widely conducted in the literature. The first studies on evaluating port services were conducted in the late 20th century by Foster (1979), Slack (1985) and Murphy and Ross (1987), who merged the concepts of PSQ and port selection by asking survey participants to identify the key factors for selecting a port.

To get a comprehensive understanding of the PSQ studies in global academic literature, this study employed a systematic literature review (SLR) approach to collect, filter and analyze relevant journal papers. The approach consisted of several key steps: (1) defining and determining appropriate keywords and databases, (2) identifying relevant papers based on the keywords, (3) retrieving the relevant papers, (4) filtering the papers, (5) analyzing the selected papers and (6) developing the conceptual framework of this study, illustrated in Figure 2.

According to Figure 2, the first step involved determining the appropriate literature databases and keywords to cover the scope of the study. The keywords were divided into two categories: Category 1 included keywords related to PSQ, ROPMIS model and port operations, while category 2 included keywords related to service quality, seaports and port geography. The inclusion criteria for the paper selection were based on these keywords. The literature searching process was conducted using Google Scholar, Scopus and Web of Science (WoS), but only papers indexed in Scopus and WoS were selected for the review process to ensure their quality. In the second step, the relevant papers were identified through the selected literature database system using the determined keywords. The third step involved retrieving and screening the relevant papers based on the study's quality and scope, and only the good-quality papers that matched the study's scope were selected. The selected papers were analyzed in the fifth and sixth steps to develop the conceptual framework of the study, where a review of statistics was conducted PSQ measurement studies were recognized and a conceptual framework was developed to highlight related gaps or issues found. Similar processes were used by other studies, such as Mehdiabadi et al. (2020), Toorajipour et al. (2021) and Xi and Hamari (2021).

After completing the filtering process, this study was able to find only 24 papers out of 35 papers retrieved from the selected databases that covered the topic of PSQ between the years 2004–2022 (See AppendixTable 6). Eleven (11) papers were excluded from this study as they did not meet the indexing and inclusion criteria set for this study. Based on the review of those 24 selected papers (See Appendix), it can be concluded that previous studies focused on four (4) different scopes, as shown in Figure 3. The scopes that most studies covered were (1) identifying PSQ determinants, (2) determining/comparing the level of PSQ, (3) developing new structural PSQ models and (4) evaluating the effects of service quality on customer satisfaction, loyalty or referral intentions.

In addition to the research on the above scopes, various PSQ measurement models were applied in the studies reviewed, including the SERVQUAL model, ROPMIS model, Kano's model, importance-performance analysis model, customer-based PSQ model and structural PSQ model. The analysis of these PSQ measurement models used in the studies reviewed is summarized in Figure 4.

In addition, the review process summarized the distribution of PSQ research by country. Figure 5 indicates that 17% of the studies on PSQ were conducted from the Korean ports' perspective, while 14% were from the Vietnamese ports' perspective, 12% from the Chinese ports' perspective and 9% from the African, Taiwanese and Singaporean ports' perspectives, among others.

However, the review process showed that no comprehensive study was conducted in the past to assess or evaluate the service quality level at the ports of Oman. This knowledge gap could be detrimental to the Omani ports, potentially hindering their opportunities to achieve the goals of Sultanate of Oman Logistics Strategy (SOLS) 2040 sustainably. Port operating companies must understand factors that satisfy their customers to ensure customer satisfaction, which is a significant output that portrays service quality in maritime transport, including the port sector (Thai, 2008, 2016; Yeo et al., 2015; Phan et al., 2021). Obtaining a high degree of customer satisfaction is essential for each port to maintain customer loyalty. According to Cho et al. (2010) and Yeo et al. (2015), customer satisfaction, loyalty and referral intention are the outcomes of good service quality. This study aims to address the gap in the literature on PSQ studies, particularly from the perspective of Omani ports.

2.3 ROPMIS model

Thai (2008) introduced ROPMIS, a PSQ measurement model that explored service quality in the maritime transport sector. The model focused on six dimensions of measurement, which were resources, outcomes, process, management, image and social responsibility. These dimensions were developed based on a comprehensive review of service quality dimensions and factors in previous studies. The ROPMIS model was found to be more applicable to the maritime industry because it included image and social responsibility, which are critical in the industry, compared to the dimensions used in the SERVQUAL model. Thai (2008) also suggested that the dimensions could be revised for specific subsectors in the maritime industry, such as ports, as the dimensions used in the ROPMIS model were relevant to the port sector. Thai (2016) identified six quality dimensions in this model.

1. Resources-related: concerns physical and financial resources, facilities and equipment conditions, location, infrastructure and other related resources.

2. Outcome-related: involves the services provided to customers, including on-time delivery of shipments and service pricing.

3. Process-related: pertains to the interaction between employees and customers, including how staff behavior is perceived by customers, their knowledge of customer needs and the use of technology to improve service.

4. Management-related: involves the efficient selection and deployment of resources to meet and exceed customer needs and expectations, employee knowledge, skills and professionalism, and transforming customer requirements into reality.

5. Image/reputation-related: relates to customers' overall perception of the service organization.

6. Social responsibility-related: concerns an organization's ethical practices and operations in behaving in a socially responsible manner.

Apart of their advantages, which are useful to be applied in the maritime industry, researchers should also be noted on their weaknesses, such as in terms of simplification and flexibility. In terms of simplification, the ROPMIS model simplifies the assessment of service quality by categorizing it into six dimensions. While this simplicity can be useful, it somehow may oversimplify the complex nature of service quality in maritime transport, where numerous factors influence the overall customer experience. On the other hand, as the model follows a predetermined set of dimensions, it may not be easily adaptable to a unique characteristics or requirements of different maritime transport operations. This lack of flexibility can limit its applicability in diverse service settings or emerging trends within the industry (Thai, 2008, 2016; Yeo et al., 2015). Due to that, any revision made for specific subsectors in the maritime industry or other industries may not produce the actual output measured. Therefore, to avoid the reliability of the data being compromised after any revision made to the model; a proper verification process should be made accordingly by including reviews of qualified field experts to validate the measurement items under each parameter involved. In addition, Cronbach Alpha's consistency test can also be conducted in the verification process to calculate the reliability of the measurement items. This verification process helps to ensure the relevancy and adequacy of measurement items under each parameter are maintained (Le-Hoang, 2020).

3.1 Research methodological framework

A framework was created for the study, which is illustrated in Figure 7, to organize research activities and outline important stages. Drawing from Figure 6, the framework provides a summary of how the dimensions of PSQ were utilized to develop relevant strategies for improving PSQ in Oman in line with the SOLS 2040.

During the research process, this study relied on qualitative information to collect quantitative data from the respondents. Qualitative information was used to verify the initial parameters or constructs in the model adopted and ensure that they were suitable for Oman's port industry perspectives. Through interviews, a final set of constructs for measurement was determined to collect quantitative data. Expert sampling technique has been applied to select only qualified experts with appropriate experience and background to validate the parameters. The main criteria of the qualified experts are the respondents should be currently working in the port industry, and in terms of experience, they should have more than 10 years of experience of services in the industry. Based on these criteria, five experts have been selected as qualified respondents to verify the parameters. Table 1 summarizes the qualitative constructs and measurement items that were finalized to facilitate the quantitative data collection process. Subsequently, a survey was conducted to collect the required quantitative data.

The study designed questionnaires to collect quantitative data, which incorporated the Likert scale to measure the responses of the participants. To ensure ease of data interpretation, this paper followed a certain procedure in determining the cell measurements for the Likert scoring. They used a range of scores from 1 to 5, giving a range of 4 (5–1 = 4). Then, they divided the range by the number of cells, which was 5, resulting in a cell length of 0.8 (5/4). As a result, the first cell length was 1 + 0.8 = 1.8, as shown in Table 2.

Using stratified and snowball sampling procedures, a total of 102 respondents were obtained for this study. These 102 respondents were selected from several cargo owners, logistics companies, freight forwarders and shipping companies because they have adequate experience of utilizing Oman's port services, which is necessary for this study to ensure that their feedback are valid and reliable for assessing the PSQ. In addition, their selections in the filtering process are also based on their working experience and background, which includes more than 5 years of experience and currently active engagement with port services in Oman. Their wide experience engaging in various port services allows them to have proper insights for evaluating the level of services provided by each port, respectively.

Based on the stratified sampling technique, the respondents have been segregated into three different backgrounds, which are the managers, supervisors, and ship navigating officers, in order to gather feedback by combining different angles of perspectives. The managers and supervisors provided their evaluations based on their experiences from the perspectives of cargo companies or freight forwarders using the port services, but from two different angles, from the management and operational sides, respectively. Meanwhile, the ship officers provided their evaluations based on their experiences in the aspects of the marine sides (i.e. ship traffic management, waiting time, turnaround time, etc.). Nevertheless, due to certain restrictions to access the respondents, especially the ship navigating officers such as port and ship security policy, a snowball sampling technique is also incorporated to support the stratified sampling process so that proper access to qualified respondents can be realized. This was successfully done with cooperation from the related company and port representatives.

Table 3 provides a breakdown of respondents by the main seaports in Oman. According to the records, 51% of the total respondents provided feedback on the service quality of Ad Duqm port, while 39.2% were for Sohar port and 9.8% were for Salalah port.

The collected data were analyzed using statistical methods after the questionnaires were retrieved. To evaluate the responses, frequency analysis and percentage distribution were used, as stated in previous studies (Abdul Rahman et al., 2016; Othman et al., 2019). Moreover, the level of PSQ was analyzed using a weighted mean. The weighted mean calculates the average of the mean of all the groups based on their respective weight (the N in each group), as shown in Eq. (1) in the article. Bluman (2012) describes the weighted mean as the weight arithmetic means of the given data groups. The sum of the mean of each group multiplied by its respective weight is divided by the total weight.

4.1 Demographic profile

Table 4 presents the demographic profile of the participants who took part in the study. The data gathered revealed that the highest percentage (40.2%) of respondents fell within the 41–50 age group. The age group of 31–40 constituted 34.3%, while only 11.8% were between 21 and 30 years old. This suggests that the respondents were mature enough to assess the PSQ and provide appropriate feedback for the survey. Concerning gender, 95.1% of the respondents were male, and only 4.9% were female. In terms of educational background, most of the respondents (73.5%) were college graduates, while only 3.9% had a high school education. In terms of job positions, 40.2% were managers, 30.39% were supervisors and 29.41% were navigating officers.

4.2 Evaluation of port service quality

The questionnaire used in this study consisted of 29 sub-variables that were combined into five variables related to the quality of port services. The values for these five criteria are shown in Table 5.

Referring to Table 5, the analyzed data can be explained as follows:

Resources: Five questions were used to measure this indicator, and a mean score of 3.59 was obtained, which was the second-highest score. The score indicates that the respondents strongly agreed that the main ports in Oman had various port resources available. They believed that the ports had modern equipment and physical infrastructure that could cater to the required services and meet the needs of their clients. Having modern facilities and equipment is important for port operators to provide efficient and excellent services that can satisfy their client's needs and wants. However, being rated “high” means that there is still room for improvement for the port operators to enhance the quality of the port services.

Outcomes: Seven questions were presented to the respondents for their assessment. After analyzing the results and referring to the summary in Table 5, it was found that the mean score for the outcome indicator was 3.51. This suggests that the respondents agreed that the port operators provided fast and reliable services, ensuring that the goods were in good condition and documents were handled properly, thereby satisfying their clients. Nonetheless, since the mean score was 3.51 out of 5, it indicates that there is still room for improvement in the reliability of service provision. This improvement is necessary for the port operators to establish solid trust among their customers and enhance customer loyalty.

Processes: Four questions related to the port process aspect were used to measure this indicator for the respondents who utilized the related services at the ports. The result is summarized in Table 3 and shows that the mean score obtained was 3.50, indicating that the respondents agreed that the port operators always responded to their inquiries and requests with good knowledge and a professional attitude. Customers look for port servicing companies that can adequately respond to their requests and solve their problems as soon as possible. However, the rating also revealed a gap of 1.5 (5.00–3.50 = 1.50), indicating that a lot needs to be done to improve the processes within the port to make it outstanding and attract more users. For instance, port servicing companies need to pay serious attention to improving their timeliness by responding quickly to customers' requests with proper manners to ensure their satisfaction with the services given.

Management: Six questions were used to measure this indicator, which recorded the lowest mean score of 3.49 compared with the other four indicators. Respondents indicated that the port operators were capable of achieving a high level of efficiency in their operations and management through the use of comprehensive ICT applications. The application of advanced technology in the port management system could make tasks and processes much easier to organize and coordinate. It also improved efficiency and accuracy in port management. The score obtained showed a gap of 1.51, which meant that companies needed to make necessary changes to improve their management systems to progress further in the global logistics network. To identify critical improvement areas in the management aspect, port operators had to collect appropriate feedback from their clients to analyze and assist in making the right decisions.

Image and social responsibility. Seven questions were used to measure this indicator, and it had the highest mean score of 3.68. According to the results, the respondents thought that the port operators in Oman presented a “very satisfactory” image and social responsibility, although there were still some areas that needed improvement. Therefore, the ports had to pay attention and be committed to achieving an excellent image and social responsibility standard.

Table 5 shows the overall evaluation of “Port Service Quality” for the three Omani ports involved. The analysis showed that all three ports in Oman had a “high” quality of port services according to the overall average rating in Table 5. However, the respondents believed that the port operators should focus on improving their services to keep up with the latest trends in global logistics development, such as advanced technological facilities and systems in the port sector. This is because the overall average rating obtained was only 3.55, indicating that there is room for improvement to make seaport operations more effective and efficient.