Social Disconnectedness and Career Advancement Impact on Performance: The Role of Employees’ Satisfaction in the Energy Sector

Abstract

Employee performance in remote areas is a source of concern for the Saudi Arabian energy sector, which serves as the primary engine of the country’s economy. This research paper aimed to study the impact of social disconnectedness and career advancement on employees’ performance through employee satisfaction as a mediator. The targeted population was employees worked in remote areas in the energy sector. Data were collected using a web-based questionnaire and distributed electronically using social media. A total of 390 respondents participated in this study, and structural equation modeling (SEM) was employed to analyze the collected data. The study findings revealed that career advancement positively impacts employee performance; however, social disconnectedness negatively impacts employees’ performance. Both career and social factors had an indirect effect on employees’ performance through employee satisfaction. Lastly, results demonstrated a positive impact of employee satisfaction on employee performance. Important insights into theoretical and practical implications were discussed.

1. Introduction

Aristotle claimed centuries before Christ that man is a social animal by nature [1]. That is, he implied that social interaction is a necessary component of human existence, and that social connectivity enhances life. Recent research has linked fragile social disconnectedness with poor health, low life satisfaction, and, sadly, suicide and premature mortality [2]. As heinous as the repercussions of ineffective social connection are, contemporary organizational structures may expose individuals to them. A case in point is employees in the energy sector in Saudi Arabia. Saudi Arabian energy companies mostly operate in remote areas in the desert, away from the cities and main roads. It is sometimes difficult to work in these locations, since humans like to socialize and be close to family and friends [3], which could lead to a huge interruption to this business, since workers who are unsatisfied will perform poorly. Of course, being isolated from coworkers does not mean that individuals are necessarily disconnected from others outside the work realm (i.e., family, friends, community peers). Employment in remote areas (i.e., occupations in the oil and energy sector) not only limits possibilities for interpersonal engagement, but social connectedness outside of work may also be limited [4]. Social connectivity beyond work is the opposite of feeling isolated and alone when things go wrong. It means being in touch with and emotionally linked to families outside of work [5,6].

Social disconnectedness has a detrimental effect on work satisfaction and organizational commitment [5] and increases turnover ratios [6]. Additionally, socially isolated employees believe that they lack mentoring and career support, which limits their prospects for project assignments and progress [7,8]. Chen and Kao [9] went further and stated that being socially isolated not only reduces job performance but also raises the risk of developing health problems and low self-esteem [10]. People have become more committed to their careers and less committed to their organizations because of changes in work conditions and the speed at which professionals move up the ladder [11]. As businesses become flatter and less capable of providing secure positions, career advancement has become a crucial source of professional meaning and continuity [12,13]. Personal differences and situational attributes are key antecedents of career advancement and employees who have high career advancement opportunities might have greater job satisfaction [14,15].

There is limited extant research that investigates the influence of social (i.e., social connectedness) and career factors (i.e., career advancement) on an employee’s performance. To the author’s knowledge, this is the first study that explores these relationships in the context of the energy sector in Sadia Arabia. This study aims to analyze these factors before the next major interruption to the Saudi energy sector and the Saudi energy economy as a whole.

The results of this study could enhance Saudi Arabia’s energy sector efficiency, because the energy industry is subject to seasonal demand changes, which can affect oil and energy companies’ workplace situations. This may have an effect on employee performance, making it more difficult to manage and recruit talent in challenging environments and remote areas. Thus, examining social and career factors and their effects on employee satisfaction and performance in Saudi Arabia would help design strategies and regulations to improve workplaces for oil and energy employees.

Furthermore, the results of this study might give suggestions to decision makers in the energy sector in general and the energy sector in Saudi Arabia context in particular. Employees in the energy sector usually work in barren areas miles away from the developed cities. The case of Saudi Arabia is very clear, as most of the energy sector companies are located in the desert. These isolations foster the perception of social disconnectedness and threaten career advancement, which usually causes job dissatisfaction and low employee performance [16]. Despite the severe effect of the spread of COVID-19, it highlights many benefits of remote working, especially in barren areas. This can encourage decision makers to design some flexible work hours to decrease the workload on site and increase the workload off site.

2. Literature Review

Employee satisfaction and performance are essential for any organization in order to meet its intended function as well as meet the stockholder’s expectations [17]. However, these two terms become extremely important for organizations that operate in very remote areas. There are several definitions for employee satisfaction as well as employee performance, which are very common terms in human resource management (HRM). An employee’s satisfaction is defined as how happy an employee is in their current workplace [18]. However, what makes the employee satisfied or dissatisfied is not only the nature of the job but also the demand that this job might have on them [19]. Employee performance is defined as how well the employee performs in all their assigned tasks and the way they are accomplished [18]. In some organizations, the nature of work requires them to operate in remote areas in the energy, healthcare, or other sectors. Remote areas are defined as those locations that are very far from the main cities and could be isolated from nearby communities. These areas usually suffer from a lack of public transportation and/or other major services, such as hotels, supermarkets, and government main offices [20]. In Saudi Arabia, there are several sectors that operate in remote areas. However, this paper focuses on Saudi energy organizations that operate in remote areas due to the nature of the energy sector, which requires them to be away from main cities for safety and security reasons. There are factors that are influencing employees’ satisfaction and performance who are working in remote areas in the Saudi energy sector. According to Herzberg’s theory of motivation, there are generally two factors affecting employee satisfaction as well as performance, which are motivating and hygienic factors. The motivator factor is mainly the one that focuses on recognition, achievement, job progress, and responsibility [21]. The hygiene factor is mainly the one that focuses on salary, policy, supervision, and working environment [22,23]. There are factors influencing employees’ satisfaction and performance in remote areas of the Saudi energy sector, which are pretty much similar to those for sectors that are operated in remote areas. First, career factors (i.e., career advancement), which are mainly concerned with opportunities and growth, as well as education, where the employee seeks to live near the educational institutes to complete their bachelor, master, or even higher degree, also seeks to work near the main headquarters for career opportunities and growth to progress in their job to reach c-suit positions [24]. The second factor is the social factor (i.e., social disconnectedness), where the employees need to socialize with their relatives. It is human nature to desire a similar lifestyle to other employees who are working in main cities [25].

2.1. Social Disconnectedness

Social connectedness refers to the subjective perception of having strong ties with the social world [26]. Based on the primary definition of a “sense of belonging and interpersonal relationships” from the previous research paper introduced by Lee and Robbins [26] (p. 338), social connectedness in this paper is defined as “intimacy and a sense of belonging with friends, family, and the community in the home environment while working in remote areas”. Hong et al. [27] described connectedness as a multidimensional structure that contributes significantly in promoting self-esteem, happiness, and confidence. Social life has an effect on employee satisfaction as well as performance, especially for employees who work in very remote areas [20]. Workers who are socially isolated have poor job performance, since their minds are busy thinking about relatives and friends [20]. Additionally, in remote areas, there are limited schools and educational levels for workers’ children to pursue their normal education, and this is another factor that effects both job satisfaction as well as job performance [28]. Because it satisfies a fundamental human desire for interpersonal relatedness, social connectedness is a significant antecedent of motivation and quality of life [29]. Undoubtedly, dysfunctional relationships with people such as family partners can have great negative impacts on physical and mental health [30]. Regular contact with family and friends (who are unrelated to the job) is, however, substantially associated with satisfaction and happiness [29]. The research on work–family enrichment strengthens this idea, indicating that positive family connectedness may boost affective reactions at work [31]. Furthermore, Ref. [32] highlighted the negative impact of working in remote areas on staff wellbeing and satisfaction.

There is a strategy currently being studied to overcome the social disconnectedness issue, which is having long annual leave for workers in the energy sector to give them time to socialize with their relatives and friends. However, this has still not been proven successful and remains a social factor influencing employee satisfaction and performance, since the employees have limited opportunity to socialize with their relatives and friends since they are working in very remote areas [33]. Moreover, human resource specialists are studying the option of having flexible working hours to encourage people to work in remote areas as well as to overcome this challenge that might impact employee performance [34]. Hence, as shown in Figure 1, it can be hypothesized that:

Hypothesis 1 (H1).

Social disconnectedness negatively impacts employees’ performance.

2.2. Career Advancement

Career advancement, which is mainly concerned with job advancement opportunities and growth, is affecting employee satisfaction and performance for those who work in remote areas [35]. Workers in remote areas will face challenges in pursuing advanced degrees, whether diploma, bachelor’s, master’s, or PhD, because they are far from institutional hubs, which are typically located in major cities [35]. The study by [36] highlighted the shortage and the high turnover rate of the workforce in Australian remote areas and found that the causes might be due to limited career advancement opportunities.

According to [37], which was a study of Indian workers in remote areas, advanced degrees and other training and development courses are the main factors for job satisfaction, and hence, they will positively influence job performance. The government and companies in the energy sector introduce a number of strategies to overcome growth issues for workers in remote areas, one of which is open and free access to some libraries to help develop and satisfy the needs of workers who are interested in books and self-learning [38]. Additionally, distanced learning is provided by some companies and the government for workers in remote areas to pursue advanced degrees, which will help them to get away from career isolation at remote locations [20]. Despite these strategies from the government and companies to overcome growth in remote areas, employees’ satisfaction and performance may be negatively impacted since they do not have the same opportunities for growth compared to those who work in main cities [19].

On the other hand, career opportunities are an obsession for many workers in remote areas, especially in the energy sector. Usually, employees are looking for career growth to climb the ladder to higher positions, and this would be difficult to achieve in remote areas [29]. This is because there are usually no higher-level jobs in remote areas; they are limited to supervisory level at most, and this is almost always the case in all energy companies that operate in remote areas [39].Therefore, job satisfaction and performance are affected by the limitation of the availability of higher positions and career opportunities, especially for workers who have the ambition to reach the C-suit level or other ward executive level, according to a survey done in the USA for workers in remote areas in the energy sector [20]. Several strategies have been made by decision makers in energy sector companies, one of which is to have rotational assignments for high-potential employees to serve in remote areas for certain years. Then, if they pass some leadership tests, they can be moved to headquarters in main cities to pursue leadership positions and achieve career opportunities [40]. Despite these strategies from energy companies to overcome growth in remote areas, employee satisfaction and performance are impacted, since the employees have very limited opportunities for promotion as C-suit compared to those who work in main cities [28].

Hypothesis 2 (H2).

Career advancement positively impacts employees’ performance.

2.3. Job Satisfaction and Employee Performance

Job satisfaction refers to an employee’s good attitude [41,42] or favorable emotion toward the activity performed [43], which improves the working environment, and thus, contributes to a positive ambiance in the workplace [44]. This attitude implies an elevated level of employee well-being and is frequently related to a desire to demonstrate greater commitment to the firm [45]. A happy employee is less likely to leave the company [46,47], putting in significant effort not only to improve integration, but also to represent the company with dignity and pride [46]. Job satisfaction is viewed positively as a predictor of employee performance [48] or as a component of employee happiness at work [49]. This employee mindset [50] is critical for human resource managers who recognize that retaining employees and boosting engagement and performance are contingent upon job satisfaction [46,51,52].

Employees’ satisfaction was found to be able to mitigate the negative impact of social disconnectedness on employees’ performance [53] and can improve the positive impact of career advancement on employees’ performance [54]. Employee satisfaction has a magnificent influence on employee performance, where the satisfied employees will be engaged in day-to-day business and will perform better than unsatisfied employees in all business aspects [55]. This is in contrast with unsatisfied employees, who are made to do simple jobs even if they are smart and high performing. This is mainly due to less focus on their job because they are not happy, engaged, and aligned with the organization’s goals and objectives. Based on these arguments, the following hypotheses can be introduced:

Hypothesis 3 (H3).

Employees’ job satisfaction mediates the relationship between social disconnectedness and employee performance.

Hypothesis 4 (H4).

Employees’ job satisfaction mediates the relationship between career advancement and employee performance.

Hypothesis 5 (H5).

Employees’ job satisfaction positively affects employees’ performance.

3. Methodology

3.1. Instrument Measurement

The research instrument was derived from previous studies and has five sections. The first one is about demographic data, which covers age, nationality, gender, level of education, marital status, salary, and service time. The second section is about employee satisfaction; the generic job satisfaction scales were used for this part of the questionnaires [56]. The third section is about employee performance, where the Individual Work Performance Questionnaire was used with minor amendments to suit the selected context [57]. The fourth section describes social connectedness and contains seven items derived from the Social Connectedness and the Social Assurance Scales introduced by [26] with minor amendments to suit the selected context. Finally, the last section explains career advancement and has six items derived from [58], with minor amendments to suit the selected context.

Likert scales that ranged from one (strongly disagree) to five (strongly agree), with one being the lowest and five being the highest possible score, were employed in the study instrument. Seven employees and four academics tested the employed instrument for content validity. The instrument was pilot tested to ensure its applicability, readability, and comprehension. It was stated clearly in the questionnaire that the answers would be kept strictly personal and anonymous. Because the study relies on self-reporting instrument, common method variance (CMV) may be a concern. [59]. To evade any probable CMV issue, Harman single-factor analysis method was employed, in which the number of retained dimensions was fixed to one without any rotation method. The result signals that CMV is not a problem in this study, as one factor emerged to explain only 35% of the variance.

3.2. Participants and Data Collection

The population of this study is all full-time non-managerial workers in Saudi Arabia’s energy sector in remote areas. Since there are no accurate data for the number of employees working in remote areas in the Saudi energy sector, the sample size should be around 370, according to Krejcie and Morgan [60], assuming the number of employees is more than 10,000. With several difficulties and governmental approvals to approach a larger number of employees working in remote areas, our research team successfully collected 390 valid responses.

In order to conduct SEM testing, the study needs at least a sample size of 390 participants, which met Nunnally’s [61] condition of at least 10 responders for each question. The current study scale has 29 items (questions); therefore, the sample size surpassed the suggested 290 responses, and the sample size of 390 meets to the conditions suggested by Hair et al. [59] for a at least 100 to 150 responses to have satisfactory estimations and results. Furthermore, Krejcie and Morgan [60] recommended a sample size of at least 384 when the targeted population surpasses 1,000,000; the current study had a sample size of 390, beyond all the guidelines and adequate for further analysis. The primary advantage of using SEM data analysis is that it enables the assessment of the study variables’ interdependence assumptions.

4. Data Analysis Results

4.1. Descriptive Statistics

This part identifies and summarizes the demographic characteristics of the sample.

Table 1. Demographic characteristics of the sample.

Variables	Categories	N = 390	%
Age	Less than 30 years old	122	31.1
	30–40 years old	203	52.5
	40–50 years old	52	13.2
	Above 50 years old	13	3.2
Education	High school	33	8.7
	Diploma	44	11.4
	Bachelor	227	58.0
	Masters and above	86	21.9
Gender	Female	21	5.5
	Male	387	94.5
Marital Status	Single	98	25.1
	Married with no kids	55	14.2
	Married with kids	228	58.4
	Divorced kids	9	2.3
Nationality	Non-Saudi	6	1.4
	Saudi	384	98.6
Salary/Month	Less than 15,000 SAR	108	27.9
	15,000–25,000 SAR	201	51.6
	25,000–35,000 SAR	63	16.0
	Above 35,000 SAR	18	4.6
Working Experience/years	0–5	231	59.4
	5–10	86	21.9
	10–15	34	8.7
	15 and above	39	10.0

results revealed that more than half of the study population were in the age categories of 30 and 40 years old (52.5%), followed by employees aged less than 30 years old (31.1%), and a few aged above 50 years old (3.2%). More than half had a bachelor’s degree (58.0%), and few were in high school (3.2%). The majority of the employees were males (94.5%). Most of the employees were married with kids (58.4%), followed by single employees (25.1%), while a few (2.3%) were divorced with kids. Almost all the employees were Saudi nationals (98.6%). More than half of the employees (51.6%) were paid between 4000 and 6000 USD/month, while very few (4.6%) had a salary above 9000 USD/month. Most of the employees (59.4%) had been working in the remote areas for less than five years, while a few had done so between 10 and 15 years (8.7%). The obtained answers were between five to one, with five means “strongly agree” and one means “strongly disagree”. The mean ranged from 3.41 and 4.03, while the standard deviations were found to be between 0.890 and 1.176, indicating that the collected data were more distributed and less focused around its mean [62]. The kurtosis and skewness output (scores distribution) showed that no values were found to exceed +2 or less than −2, proposing a normal univariate distribution [63], as depicted in

Table 2. Descriptive analysis (n = 390).

Abbreviation	Items	Min.	Max.	M	S. D	Skewness	Kurtosis
Job satisfaction (Macdonald and Maclntyre, 1997)
Satis_1	I receive recognition for a job well done.	1	5	3.49	1.108	−0.948-	−0.132-
Satis_2	I feel close to the people at work.	1	5	3.41	1.157	−0.847-	−0.511-
Satis_3	I feel good about working at this company.	1	5	3.58	1.048	−1.109-	0.287
Satis_4	I feel secure about my job.	1	5	3.62	1.076	−1.042-	0.178
Satis_5	I believe management is concerned about me.	1	5	3.43	1.176	−0.925-	−0.376-
Satis_6	On the whole, I believe work is good for my physical heath.	1	5	3.41	1.111	−0.851-	−0.414-
Satis_7	My wages are good.	1	5	3.53	1.096	−1.039-	0.025
Satis_8	All my talents and skills are used at work.	1	5	3.52	1.084	−0.988-	0.001
Satis_9	I get along with my supervisors.	1	5	3.48	1.110	−0.896-	−0.319-
Satis_10	I feel good about my job.	1	5	3.47	1.142	−0.923-	−0.308-
Employee’s performance (Koopmans, 2013)
Perf_1	I worked towards the end result of my work.	1	5	3.91	0.928	−1.583-	1.931
Perf_2	I kept in mind the results that I had to achieve in my work.	1	5	3.92	0.898	−1.618-	1.247
Perf_3	I was able to separate main issues from side issues at work.	1	5	3.92	0.899	−1.613-	1.225
Perf_4	I was able to fulfil my responsibilities.	1	5	3.92	0.900	−1.600-	1.176
Perf_5	I have demonstrated flexibility.	1	5	3.93	0.903	−1.603-	1.182
Perf_6	I worked at keeping my job skills up to date.	1	5	3.93	0.890	−1.605-	1.283
Perf_7	I focused on the positive aspects of a work situation, instead of on the negative aspects.	1	5	3.93	0.890	−1.605-	1.283
Social connectedness (Lee and Robbins, 1995)
Soci_1	I feel more comfortable when someone from my family is constantly with me.	1	5	3.68	1.146	−0.990-	0.146
Soci_2	My life is incomplete without a buddy beside me.	1	5	3.69	1.130	−1.026-	0.273
Soci_3	It’s hard for me to use my skills and talents without someone beside me.	1	5	3.69	1.126	−1.017-	0.249
Soci_4	I stick to my friends and family like glue.	1	5	3.68	1.133	−1.011-	0.218
Soci_5	I join groups more for the friendship than the activity itself.	1	5	3.69	1.128	−1.014-	0.241
Soci_6	I wish to find someone who can be with me all the time.	1	5	3.69	1.122	−1.025-	0.285
Career advancement (Amatea, 1986)
Care_1	I expect my job/career to give me more real satisfaction than anything else I do.	1	5	3.94	1.204	−1.291-	0.752
Care_2	Building a name and reputation for myself through work/a career is one of my life goals.	1	5	4.01	1.170	−1.437-	1.286
Care_3	It is important to me to feel successful in my work/career.	1	5	4.02	1.170	−1.447-	1.322
Care_4	I want to work, but I do not want to have a demanding career.	1	5	4.02	1.163	−1.441-	1.327
Care_5	I expect to make as many sacrifices as are necessary in order to advance in my work/career.	1	5	4.03	1.164	−1.452-	1.352
Care_6	I expect to devote a significant amount of my time to building my career and developing the skills necessary to advance in my career.	1	5	4.02	1.161	−1.450-	1.355

.

4.2. Confirmatory Factor Analysis (CFA)

A first-order CFA test was carried out using the maximum likelihood (ML) estimate technique in order to determine the scale’s convergent and discriminant validity, respectively. Four dimensions (social disconnectedness, career advancement, job satisfaction, and employee performance) were subjected to CFA along with their related indicators. To evaluate the fit of both measurement and structural models, several goodness-of-fit (GoF) measures, including those provided by [62,64,65], were applied: “normed chi-square” (chi-square/degree of freedom), “Tucker–Lewis index” (TLI), “comparative fit index” (CFI), “standardized root mean squared” (SRMR), “root mean square error approximation” (RMSEA), and “parsimony comparative fit” (PNFI). The results of the CFA’s goodness-of-fit analysis suggested that the model’s fit was acceptable (see

Table 3. First-order factor analysis convergent and discriminant validity.

Factors and Items	Loading	CR	AVE	MSV	1	2	3	4
1—Job satisfaction (a = 0.955)		0.960	0.827	0.043	0.893
Satis_1	0.926
Satis_2	0.859
Satis_3	0.942
Satis_4	0.859
Satis_5	0.946
Satis_6	0.835
Satis_7	0.892
Satis_8	0.961
Satis_9	0.980
Satis_10	0.969
2—Employee’s performance (a = 0.936)		0.975	0.848	0.144	0.269	0.921
Perf_1	0.858
Perf_2	0.912
Perf_3	0.944
Perf_4	0.906
Perf_5	0.930
Perf_6	0.950
Perf_7	0.946
3—Social connectedness (a = 0.927)		0.980	0.890	0.118	0.047	0.342	0.943
Soci_1	0.927
Soci_2	0.946
Soci_3	0.950
Soci_4	0.930
Soci_5	0.954
Soci_6	0.951
4—Career advancement (a = 0.938)		0.975	0.867	0.144	0.147	0.379	0.344	0.931
Care_1	0.834
Care_2	0.944
Care_3	0.941
Care_4	0.940
Care_5	0.966
Care_6	0.960

Model fit: (χ² (371, N = 390) = 1236.543, p < 0.001, normed χ² = 3.333, RMSEA = 0.038, SRMR = 0.037, CFI = 0.965, TLI = 0.934, NFI = 0.956, PCFI = 0.608 and PNFI = 0.600). CR: composite reliability; AVE: average variance extracted; MSV: maximum shared value; diagonal values: the square root of AVE for each dimension; below diagonal values: intercorrelation between dimensions.

). For the purpose of determining construct reliability, composite reliability (CR) and Cronbach’s alpha values were calculated. The four dimensions employed in this study had the following CR scores, as depicted in Table 3: social disconnectedness (0.980), career advancement (0.975), job satisfaction (0.960), and employee performance (0.975). All of the CR results were more than the 0.70 cut-off value that was specified, indicating adequate internal consistency [63].

Furthermore, the measuring scale convergent validity was supported because all items had high factor loadings (FL) that were statistically significant (Table 3). As shown in Table 3, the FL scores ranged from 0.834 to 0.980, which was higher than the recommended threshold of 0.50 [64]. Furthermore, the AVE scores for all employed factors (social disconnectedness, career advancement, job satisfaction, and employee performance) were 0.890, 0.867, 0.827, and 0.848, respectively (Table 3). All AVE values were greater than 0.50, indicating that the convergent validity was satisfactory [61]. It was also discovered that the values of AVE were greater than all of the scores for “maximum shared variance” (MSV) in Table 3, indicating that the discriminant validity was satisfactory [65]. The AVE square root for each dimension was greater than the intercorrelation scores between dimensions, providing additional evidence to suggest a high degree of discriminant validity [62,65] (Table 3).

4.3. Structural Model Results

This study employed a confirmatory approach in which a thorough literature research was conducted to help in designing the theoretical conceptual model, which was then tested against the primary collected data [61]. The predefined theoretical model either supported or rejected based on certain model fit measures. As depicted in

Table 4. The structural model results.

	Hypotheses					Beta (β)	C-R (t-Value)	Hypotheses Results
H1	Social disconnectedness			Employee performance		−0.35 ***	−9.541	Supported
H2	Career advancement			Employee performance		0.41 ***	10.351	Supported
H3	Social disconnectedness		Job satisfaction		Employee performance	Path 1: β = −0.37 *** Path 2: β = 0.49 ***	Path 1: t-value = −9.334 Path 2: t-value = 12.145	Supported
H4	Career advancement		Job satisfaction		Employee performance	Path 1: β = 0.45 *** Path 2: β = 0.49 ***	Path 1: t-value = 11.441 Path 2: t-value = 12.145	Supported
H5	Job satisfaction				Employee performance	0.49 ***	12.145	Supported
Employee performance

Model fit: (χ² (372, N = 390) = 1610.760, p < 0.001, normed χ² = 4.343, RMSEA = 0.048, SRMR = 0.047, CFI = 0.937, TLI = 0.930, NFI = 0.936, PCFI = 0.678 and PNFI = 0.610). ***: significant level is less than 0.001.

, the structural model matched the primary data (2 (372, 390) = 1610.760, p < 0.001, normed 2 = 4.343, RMSEA = 0.048, SRMR = 0.047, CFI = 0.937, TLI = 0.930, NFI = 0.936, PCFI = 0.678, and PNFI = 0.610). Following the achievement of a reasonable model fit, the study hypotheses were evaluated. Each of the relationships depicted in Figure 2 represents a certain hypothesis.

Each path between the latent variables is a hypothesis. In this regard, it is worth mentioning that we typically test the null hypothesis (no association exists) and reject it if the p-value is less than the significance level (i.e., t > 1.96) and accept it if the p-value is more than the significance level (i.e., t > 1.96) [62]. The primary factor affecting whether a hypothesis is accepted or rejected is the significance of the standardized coefficient values. The current study used significance levels of less than 0.05, 0.01, and 0.001; the lower the level of significance, the more data must diverge from the null hypothesis (no link exists). As a result, the 0.001 level of significance is more conservative than the 0.01 level of significance.

Three direct and two indirect hypotheses were proposed in this paper, as depicted in Figure 2. The first direct hypothesis, which tests the impact of social disconnectedness on employee performance (H1), is supported (t-value = −9.541, p < 0.001) with a significant negative path coefficient of −0.35, indicating a negative direct relationship between the two latent dimensions. Likewise, the SEM results indicated that career advancement has a positive significant impact on employee performance (H2) (t-value = 10.351, p < 0.001) with a high path coefficient of 0.41, thus supporting the second proposed hypothesis (H2). Furthermore, hypothesis five tested the influence of job satisfaction on employee performance; the SEM output showed a positive direct and significant (t-value = 12.145, p < 0.001) association between the two latent dimensions with a high path coefficient of 0.49, thus confirming the fifth proposed hypothesis (H5).

To examine the mediation role of job satisfaction in the relationship between social disconnectedness, career advancement, and employee performance [66,67], suggestions were followed. Zhao et al. [67] suggested that for “direct-only non-mediation” impacts, only direct path coefficients with a significant p-value should appear in the results; for “complementary mediation”, both indirect and direct associations should have a positive p-value and the same sign. Finally, “competitive mediation” is confirmed when the direct and indirect relationships are statistically significant and have different signs.

As depicted in Figure 2, the direct path from social disconnectedness to employee performance is statistically significant and negative (−0.35, p < 0.001); similarly, the path from social disconnectedness to employee satisfaction was statistically significant and negative (−0.37, p < 0.001). However the path from job satisfaction and employee performance was found to be positive and significant (0.49, p < 0.001), as direct and indirect relationship were found to be statistically significant with opposing signs; thus, competitive mediation was achieved. On the other hand, as shown in Figure 2, the direct relationship between career advancement and employees’ performance (0.41, p < 0.001) and the indirect path through job satisfaction (path one = 0.45, p < 0.001; path two= 0.49, p < 0.0012) were found to be positive and significant with the same positive sign; therefore, complementary mediation was supported. Finally, the structural model had a high degree of explanatory power (R2), explaining 55% of the variance in employees’ performance (Table 4).

5. Discussion

The objective of this research paper was to study the relationship between social disconnectedness and career advancement that influence employee performance while working in remote areas of the Saudi energy sector as well as determine the role of employee satisfaction as a mediating factor between career and social factors and employee performance. This study was able to determine that career advancement and social disconnectedness statistically influenced employee performance. The study findings revealed that there was a positive and significant relationship between career advancement and employee performance. However, social disconnectedness was found to have a negative and significant influence on employee performance. The results further demonstrated that employee satisfaction played a mediating role in the relationship between career advancement (complementary mediation), social disconnectedness (competitive mediation), and employee performance. Lastly, the results demonstrated a positive impact of employee satisfaction on employee performance.

The study findings are partially aligned with the findings of [33,68], who concluded that job performance is influenced by financial factors, such as career advancement and growth, and career factors (i.e., work conditions and wages), which enhance satisfaction and performance. However, financial factors alone are not sufficient to improve employee performance in remote areas. It should be integrated into one incentive system that has both financial and non-financial factors, including improving social life in remote areas. This is also in line with the findings by Rao [36], who showed that financial support is key for employee performance in remote areas. However, this factor alone will not work, since the employees are frustrated by a lack of infrastructure as well as social isolation, career growth, and advancement.

The existing study findings are also aligned with those of [25], who implemented their study on health workers in remote areas, where career advancement and social connectedness are essential for employee retention, which led to better employee performance. Additionally, they mentioned that other factors, such as the good relationship between the employees and themselves, as well as the availability of information and communication technology, will help in improving employee performance in remote areas. This can be further considered in the current study context in which employees in the Saudi energy sector are working in remote areas to support their companies’ operations. Therefore, the findings from the existing study and those conducted by [25,69] are aligned when it comes to social and career factors and their influence on employee performance, where work–life balance (i.e., balancing career and social factors) enhances satisfaction and performance.

The current findings are partially aligned with those of [28] that were conducted on medical students to gauge their willingness to practice in very remote areas. The study by Budhathoki [28] revealed that social connectedness is not the only factor that influences employee performance; there are other factors as well, such as high workloads in remote areas compared to main cities, poor facility management, and a lack of infrastructure. Additionally, employee satisfaction was found to be beneficial in mitigating the negative effect of social disconnectedness on employee performance [51], enhance the favorable effect of career development on employee performance [52], and increase social proximity, which can fosters employee performance [70].

Furthermore, our findings are consistent with [71], who concluded that social and peer communication programs were generally effective at improving employee engagement, satisfaction, and performance, while the deleterious role of social isolation or disconnectedness leads to decreased work productivity, which, in turn, is related to job satisfaction [72].

Finally, these study findings are consistent with Buykx’s [73] systematic review paper on the role of satisfaction in employee performance and retention. Job satisfaction is viewed positively as a predictor of employee performance [74] or as a component of employee happiness at work [75].

6. Conclusions

This paper aimed to study the relationship between social disconnectedness and career advancement and how it influences employee performance while working in remote areas within the Saudi energy sector. The study also highlighted the mediating role of job satisfaction in these relations. A total of 390 surveys were analyzed using SEM. This article takes a first step in examining energy industry workers from the perspectives of social variables (i.e., social disconnectedness) and career factors (i.e., career development) and their effects on job satisfaction and performance. In this regard, the findings are significant for understanding the working conditions of these organizations’ employees. Additionally, these findings may serve as a springboard for future research in this area, as well as for replication and comparison in other nations, or groups of countries.

The study findings revealed that there was a positive and significant relationship between career advancement and employee performance. A positive influence of career advancement demonstrated by a one-unit change in career advancement resulted in an increase in employee performance by 0.41 units. Social disconnectedness, on the other hand, was found to have a significant negative impact: a one-unit increase in social disconnectedness caused the employee’s performance to decrease by 0.35 units. The results further demonstrated that employee satisfaction can mitigate the negative impact of social disconnectedness on employees’ performance and foster the positive impact of career advancement on employees’ performance. Additionally, the results demonstrated a positive impact of employee satisfaction on employee performance. A one-unit increase in employee satisfaction causes employee performance to increase by 0.49 units. In conclusion, all the examined variables explain around 55% of the variance in employees’ performance.

To the best of the author’s knowledge, this is the first study to investigate social disconnectedness and career advancement impacts on employees’ performance in the context of the energy sector in Saudi Arabia. Exploring such relationships can facilitate the design of strategies and policies that improve oil and energy sector employees’ workplaces.

Furthermore, the findings of this study may help decision makers in the energy sector in general and in Saudi Arabia in particular. Isolated employees in this sector have a severe feeling of social disconnectedness and their career advancement is stagnate, which frequently produces workplace discontent and poor employee performance. Despite the devastating effects of COVID-19, remote work has several advantages, especially in distant areas. This may inspire decision makers to create flexible work hours to reduce on-site workload and enhance off-site workload.

7. Limitation

The shortcomings of the study can be addressed by future studies. This study examined two dimensions as possible antecedents of job satisfaction and employee performance. However, several other factors, such as job stability, organization culture, management support, and job motivation, may also impact employees’ performance. They are, however, not included in the study. The scope of this research can be investigated by incorporating a broader range of factors affecting employee performance, and additional studies may also employ some alternative research methodologies (e.g., qualitative research) to support and validate the current study’s findings.

Additionally, further research might be conducted to test not just the antecedents of the employee’s performance but also its outcomes, such as organization performance and competitive advantage. The study results were based on self-reported questionnaires (employees’ subjective points of view), which might have potential bias. Therefore, future studies can collect objective data and compare the results with the current study. A causal relationship between variables cannot be determined because the data are cross-sectional. Our study’s proposed model might also be supported by longitudinal data or data from several sources, although we avoided CMV, as suggested by [59]. Employing a multi-group analysis method can be further used to compare the results in different context [76]. Finally, this study was conducted during the spear of the COVID-19 pandemic, which might have influenced the Saudi energy sector employees’ perceptions toward factors influencing job satisfaction and performance, since most of them stayed a long time in remote areas without vacations or even weekends during the pandemic to support their companies’ operations and the overall economy of Saudi Arabia.