The Strategic Performance Measurement System and Organisational Performance Through the Lenses of Contextual Factors: Empirical Evidence from the Hotel Industry

An organisation’s external environment is one of the critical factors that determines the suitability of a specific PMS (Chenhall, 2006; Nudurupati et al., 2021). Changes in an organisation’s external environment will lead to changes in its informational needs, which will, in turn, shape its use of a PMS (Henri & Wouters, 2020). Bititci et al. (2018) noted that organisational managers need a PMS to obtain current information in a dynamic environment. Thus, given the environmental conditions of today, financial performance measures have been found to be largely ineffective for assessing organisational performance because they only reflect an organisation’s past activities (Kaplan & Norton, 2010). In an uncertain business environment, these measures are inadequate as they fail to evaluate other important performance-related areas, such as customer base, market share, and business operations. Therefore, integrating nonfinancial measures within performance measurement practices has been stressed as crucial for an organisation’s long-term success (Kaplan & Norton, 2010; Sainaghi, 2010).

Gosselin (2011) reported that when there was uncertainty in the manufacturing business environment, managers had a greater tendency to adopt the BSC. Nevertheless, a number of studies have revealed an insignificant relationship between EEU and performance measurement techniques. To illustrate, Ahmad and Zabri (2016) found that an uncertain environment surrounding manufacturing firms in Malaysia did not affect the use of nonfinancial performance measures. In addition to these inconsistent findings, a review of the literature indicated that this issue has received little attention in the context of the hotel industry, with the exception of a study conducted by Arasli et al. (2019). In this study, the authors researched various five-star resort hotels in the Antalya region of Turkey, demonstrating that environmental uncertainty was mainly related to financial, customer, and operational measures. Moreover, the association between environmental uncertainty and the use of customer and marketing performance measures was not supported by McManus (2013).

It is evident that the aforementioned studies have produced inconsistent outcomes. Hotel organisations’ surrounding environment is characterised by a high level of uncertainty and complexity and varied customer interaction. However, unlike past crises that the hotel industry has faced, the COVID-19 pandemic has caused tremendous challenges. Thus, given the changing future of the hotel industry and its dependency on the external environment, it is critical for hotel organisations to implement a strategic PMS that provides environmental information to reveal a complete picture of hotels’ performance, such as the BSC. Consequently, it is important to determine how the BSC meets the current demands of the uncertain environment surrounding hotel organisations. The following hypothesis was thus proposed:

Hypothesis 1: EEU is positively related to the use of the (a) financial, (b) customer, (c) internal business process, and (d) innovation and learning dimensions of the BSC in hotels.

The existing literature states that differences in organisational structures arise from the different environmental uncertainties organisations face (Crespo et al., 2019). Thus, the external environment is influential in terms of shaping an organisation’s internal decision-making structure (Nandakumar et al., 2010). The dynamic business environment has resulted in increased managerial complexity, which has, in turn, created the conditions for power and control delegation. For instance, Uyar and Kuzey (2016) demonstrated that decentralised decision-making is related to environmental uncertainty. Furthermore, a recent study specified the importance of an organisation’s decentralised decision-making in an unpredictable environment (Chaib Lababidi et al., 2020).

Bangchokdee and Mia (2016) reported that decentralised decision-making in hotels enables flexible and speedy responses to the external environment and recommended that this relationship be further investigated within the hotel context. Until recently, customer interaction has been an inevitable factor for the hotel industry as the provision of services and the presence of customers occur simultaneously (Pavlatos, 2015). However, this situation has changed due to the increased use of technology and the requirement to reduce physical interaction to a minimum as a result of COVID-19 (Garrido-Moreno et al., 2021). Therefore, given the latest developments in the industry, this article examined whether EEU remains a determinant of decentralised decision-making. Hypothesis 2 was thus proposed:

Hypothesis 2: EEU is positively related to decentralised decision-making in hotels.

Organisational structure is a central variable from a managerial contingency perspective and has long been researched (Chaib Lababidi et al., 2020; Chenhall, 2006; Crespo et al., 2019). A centralised organisational structure is described in terms of centralised decision-making and strictly adhering to formal rules and procedures. Meanwhile, a decentralised structure is defined in terms of the authorisation of middle managers to take responsibility for decision-making, with less emphasis placed on formal rules and procedures (Nandakumar et al., 2010). Various studies have found an association between decentralised decision-making and financially denominated performance measures (e.g. Crespo et al., 2019), whereas others have demonstrated the exact opposite (e.g. Bangchokdee & Mia, 2016). The argument for the latter is that managers do not find financial performance measures to be sufficient to base their decisions solely on them. In organisations with a decentralised structure, senior managers need reliable performance measures to examine whether the delegated decisions taken are optimal for the organisation (Bangchokdee & Mia, 2016). In this context, numerous studies have investigated the determining role of decentralised decision-making on different types of PMSs (Henri & Wouters, 2020; McManus, 2013). For example, Pavlatos (2018) found a significant positive relationship between the decentralisation of decision-making in service firms and strategic cost management. However, Gosselin (2011) was unable to confirm the relationship between manufacturing organisations’ decentralised decision-making and the BSC. Given that, in terms of the BSC, the relevant research remains limited in the hotel industry and that the findings of the aforementioned studies have been largely inconsistent, investigating whether decentralised decision-making in hotels creates a need for the BSC is a worthy pursuit. Thus, the following hypothesis was proposed:

Hypothesis 3: Decentralised decision-making is positively related to the use of the (a) financial, (b) customer, (c) internal business process, and (d) innovation and learning dimensions of the BSC in hotels.

Hotel performance and PMSs have attracted an increasing amount of attention in recent years (Sainaghi, Köseoglu, et al., 2019). Financial performance measures are easily obtained due to their quantitative and historical nature, whereas nonfinancial performance is more difficult to accurately determine (Sainaghi, Phillips, & d’Angella, 2019). The nonfinancial measures provide diverse information on customers, business operations, and employees (Henri & Wouters, 2020), all of which is crucial to the determination of an organisation’s future performance. Therefore, integrated PMSs are being regarded as increasingly important among organisations, as they play an essential role in capturing the different aspects of organisational performance. In this context, the BSC reveals an organisation’s performance level through a number of main dimensions—innovation and learning, internal business processes, and customers—and then relates the outcomes to its financial performance. For example, the indicators within the innovation and learning dimension indicate the level of qualified hotel staff, which is crucial to providing quality service to guests in a timely manner, meaning that guests will be satisfied with the hotel’s services, which will, in turn, reflect positively on its financial returns. Thus, the system enables organisations to both achieve their desired performance and support their long-term strategy.

Although the literature indicated that the association between various PMSs and organisational performance has been extensively explored, inconsistent findings have been reported. Some studies have reported a positive relationship (e.g. Arasli et al., 2019), whereas others have revealed insignificant outcomes (e.g. McManus, 2013). Bititci et al. (2018) underlined that this issue should not be neglected because it remains largely inconclusive, especially in relation to the hotel industry (Sainaghi, Köseoglu, et al., 2019), where major operational changes have occurred due to the COVID-19 pandemic. Similarly, Elbanna et al. (2015) underlined that research on the role of the BSC in hotel performance remains inadequate and called for more empirical research. One exception is the study conducted by Arasli et al. (2019), which found a positive relationship between the adoption of the BSC and performance in five-star resort hotels. Thus, expecting similar results, this research examined whether the BSC continues to assist in improving hotel performance. Therefore, the following hypothesis was proposed:

Hypothesis 4: The use of the (a) financial, (b) customer, (c) internal business process, and (d) innovation and learning dimensions of the BSC is positively related to hotel performance.

In an unstable environment, organisations are unable to precisely predict what awaits them. Decentralised decision-making enables timely and effective actions to be taken under changing conditions; thus, it enables authorised managers to deal with any uncertainty that arises in the environment (Chaib Lababidi et al., 2020; Crespo et al., 2019), which highlights the necessity of advanced PMSs. With respect to this, Uyar and Kuzey (2016) reported the mediating role of decentralised decision-making in relation to EEU and budget use. To understand the effectiveness of decentralised decision-making in the dynamic hotel industry, hotels require not only financial performance data but also nonfinancial information (Arasli et al., 2019). The BSC is believed to provide such additional information. Thus, given the current uncertainty of the external environment, implementing decentralised decision-making is likely to increase the use of the BSC. In accordance with the gap in the existing literature, this study highlights the need for further research on this issue, especially within the hotel context. Hence, the following hypothesis was proposed:

Hypothesis 5: There is a positive relationship between EEU and the use of the (a) financial, (b) customer, (c) internal business process, and (d) innovation and learning dimensions of the BSC through decentralised decision-making in hotels.

With a high level of uncertainty, organisations can implement various PMSs to obtain the information they need, which will, in turn, determine the performance outcomes. Within this context, previous studies have yielded certain empirical evidence (Uyar & Kuzey, 2016). One study related to Greek service organisations reported that environmental uncertainty was positively related to strategic cost management, which in turn had a positive impact on performance (Pavlatos, 2018). However, Hoque (2004) conducted research on specific manufacturing companies and could not find any mediating effect of nonfinancial performance measures on the association between environmental uncertainty and firm performance. This issue has not received sufficient attention in relation to the hotel industry, with the exception of the study conducted by Arasli et al. (2019). Thus, a better understanding, taking the impact of COVID-19 into consideration, is required. In today’s complicated hotel environment, this article argues that managers tend to use the BSC as it provides them with the necessary information to determine their hotel’s performance. Thus, the following hypothesis was proposed:

Hypothesis 6: There is a positive relationship between EEU and hotel performance through the use of the (a) financial, (b) customer, (c) internal business process, and (d) innovation and learning dimensions of the BSC.

Few studies have investigated the relationship between decentralised decision-making and organisation performance in relation to the mediating role of PMSs. For example, decentralised decision-making was found to be indirectly related to company performance through the mediating role of budget use (Uyar & Kuzey, 2016). Another study indicated that decentralised decision-making in hotels is only associated with better performance through the use of nonfinancial performance measures (Bangchokdee & Mia, 2016). Strategic PMSs are more important in the case of a decentralised hotel structure as it facilitates managers’ decision-making. The BSC—with its four dimensions and performance indicators—is useful to hotel managers in terms of measuring performance from a holistic perspective. However, the aforementioned studies have indicated that there remains a need for more empirical research on how decentralised decision-making affects performance through the role of the BSC. Hence, the following hypothesis was proposed:

Hypothesis 7: Decentralised decision-making is positively related to hotel performance through the use of the (a) financial, (b) customer, (c) internal business process, and (d) innovation and learning dimensions of the BSC in hotels.

This study was conducted in relation to various four- and five-star hotels in Turkey. According to the United Nations World Tourism Organization’s (2020) International Tourism Highlights, 2020 Edition, Turkey remains in the top ten of the world’s top tourism destinations. Tourism is an important contributor to Turkey’s economy and development (Köseoglu et al., 2018), making it an appropriate context for this study. Four- and five-star hotels were chosen because they attract numerous tourists due to their facilities. Additionally, larger organisations tend to use more advanced PMSs (Arasli et al., 2019). Hotels with more than 101 beds are considered large hotels (Pavlatos, 2015). In this study, hotels with between 110 and 2,800 beds were chosen, and senior hotel managers were selected as the participants. A total of 180 questionnaires were distributed to these managers; 145 were returned, yielding a response rate of 81%, which is comparable to previous studies (Hoque, 2004; Pavlatos, 2018), particularly those conducted during the COVID-19 pandemic. A member of the research team sent the online surveys by providing a link and informed the potential respondents that their participation was anonymous and that their responses would be used for academic purposes only. Moreover, pilot questionnaires were conducted to check the clarity, relevancy, and coherency of the questions before the final version of the questionnaire was distributed. The demographic details of the respondents are presented in Table 1.

The scales used were originally in English. Therefore, a back-translation method was used in which the scale items were first translated from English into Turkish and then from Turkish back into English to verify the item equivalence in each language (Brislin, 1980). In this study, EEU, decentralised decision-making, the BSC, and hotel performance were measured.

Partial least squares structural equation modelling was used to test the hypotheses as it is convenient for studies involving sophisticated models with small sample sizes, something that has seen its popularity rise in the area of management research (Crespo et al., 2019).

This study included three reflective constructs: EEU, decentralised decision-making, and hotel performance. The BSC was included in the study model as a second-order construct with its four reflective dimensions: finance, customer, internal business process, and innovation and learning. Thus, in this study, a two-stage approach was used to establish the second-order construct required to assess the measurement model of the initial framework, which consisted of seven reflective constructs (Ali et al., 2018). In the first stage, the reliability and convergent validity of the reflective measurement model were assessed by examining the outer loadings of the items associated with each construct, as well as the composite reliability (CR) and average variance extracted (AVE) (Ali al., 2018; Hair et al., 2017). To establish reliability and convergent validity, the outer loadings, CR, and AVE values should have exceeded 0.7, 0.7, and 0.5, respectively (Hair et al., 2017). However, loadings of between 0.5 and 0.7 were acceptable if the CR and AVE met the threshold (Hair et al., 2017). Table 2 shows the results for all reflective constructs that were acceptable in the first stage, indicating that reliability and convergent validity had been established.

Next, discriminant validity was determined by employing the Fornell–Larcker criterion and the heterotrait–monotrait (HTMT) approaches (Henseler et al., 2015). To assess discriminant validity, the square root of the AVE for each construct needed to be higher than its correlation with other constructs (Fornell & Larcker, 1981; Hair et al., 2017). According to Henseler et al. (2015), the HTMT value for all constructs should be lower than 0.9 to establish discriminant validity. As Tables 3 and 4 show, the results demonstrated acceptable discriminant validity based on these two approaches.

In the second stage, multicollinearity was assessed using the variance inflation factors (VIF) for the four items comprising the second-order BSC composite construct, as well as the significance of the outer weights (Hair et al., 2017). Thus, the model used in this study consisted of one second-order formative construct (BSC) and three reflective constructs (EEU, decentralised decision-making, and hotel performance). Here, the VIF should have been less than 5 and the outer weights of the composite construct’s items should have been significant to ensure that the measurement model was acceptable (Ali et al., 2018). The results indicated that the VIF values for the four items comprising the BSC were between 1.553 and 3.174, indicating low to acceptable collinearity. Furthermore, the outer weights of these items were significant. Thus, the results confirmed that the measurement model was appropriate for both the first and second stages.

Table 5 shows the results for all hypothesised relationships. The R² values for the BSC and hotel performance were 0.230 and 0.613, respectively, indicating an acceptable level of R². A bootstrapping procedure was used to assess the significance of the path coefficients (Hair et al., 2017), with the results supporting the direct effects of EEU on decentralised decision-making in hotels (H2) but not on the BSC (H1). Moreover, the results indicated the direct effect of decentralised decision-making on the BSC (H3), as well as the positive significant effect of the BSC on hotel performance (H4). With respect to the indirect effects, a product coefficients approach was applied, with the significance of the indirect effects assessed using specific bias-corrected bootstrap confidence intervals (Hayes & Scharkow, 2013). As Table 5 shows, the mediating role of decentralised decision-making on the association between EEU and the BSC (H5) was significant. Similarly, the indirect effect of decentralised decision-making on hotel performance through the BSC was significant (H7). However, the results revealed contrasting findings in terms of the indirect effect of the BSC on the relationship between EEU and hotel performance (H6).

This research was theoretically based on the integrated contingency model and examined how EEU and decentralised decision-making can be used to explain the use of the BSC, which in turn affects hotel performance, during the times of the COVID-19 pandemic. Thus, the current research contributes to the knowledge and serves as a base for future studies.

From a theoretical perspective, these findings clearly emphasise the factor of EEU, specifically the impact of the external environment on hotels’ internal decision-making structures and performance assessments. An organisation’s external environment includes various factors, including economic, sociocultural, political, legal, technological, and international factors (Arasli et al., 2019; Köseoglu et al., 2018). These factors inevitably affect organisations in terms of their internal management structures, information systems, and operational processes, and organisations generally have little to no control over these factors. Thus, as the existing literature suggests, when the environment is perceived as uncertain, organisations should adapt and use integrated PMSs to respond to the uncertainty and improve their performance. However, Aguinis and Burgi-Tian (2021) highlighted the following important issue: Measuring the performance of organisations is always challenging, especially during uncertain times. In their study, the authors reported that when organisations experience uncertainties, they need to change their strategic directions, which results in updating the PMS, although it generally takes time for the performance measures themselves to catch up. This could be a possible explanation for the nonsignificant finding in terms of the EEU–BSC–hotel performance relationship, which calls for some caution. Similarly, Nudurupati et al. (2021) stated that in today’s environmental conditions, finding a completely stable environment is unrealistic, and they classified business operating environments as either “stable/changing” or “turbulent.” While a changing environment indicates that the change occurs incrementally and can be predicted, a turbulent environment is one in which change occurs suddenly and unexpectedly, meaning that it is not predictable (Nudurupati et al., 2021).

This study supported this notion in the sense that hotels are already operating in uncertain, changing environments, which is why managers need a balanced PMS and must delegate decision-making to middle managers to have the capacity to respond to the changing environment in a timely and effective manner. However, as defined earlier, we are undeniably no longer talking about the same changing environment. The jarring effect of COVID-19 has transformed the hotel environment into one of turbulence and volatility, meaning that the BSC might no longer be immediately responsive to today’s hotel environment. Given the current turbulence in the environment caused by the pandemic, hotel organisations inherently require a greater amount of time, effort, and money to adapt their BSC.

According to the results related to a hotel’s internal management structure, decentralised decision-making is perceived to be useful to achieving efficient service processes and reveals the need for a BSC that could enhance performance. In a decentralised structure, hotels benefit from using their BSC to catch up with their internal environment and achieve better performance.

All of these consequences have converged into a perspective wherein being resilient to suddenly emerging situations has become increasingly important.

The findings of this study will be informative for hotel managers in four- and five-star hotels in Turkey. Although the EEU-related findings contradicted the BSC-related proposition, this was perhaps not surprising given the situation of the COVID-19 pandemic. First, this study noted that in the presence of EEU, decentralised decision-making is used in hotels and acts as an antecedent of the BSC and the subsequent hotel performance. The inference from these outcomes is that hotel managers should continue to maintain a decentralised structure due to its flexibility, which enables them to delegate some responsibility to middle managers to ensure efficient operational processes during the times of crisis.

COVID-19 has provided an important lesson for managers in understanding the importance of operational resilience and has shown managers continue to implement decentralised decision-making. Furthermore, the BSC must be designed to match environmental requirements. EEU has reached a completely different dimension due to the pandemic and has resulted in challenges to the effective implementation of the BSC. This is mainly because environmental conditions are changing quickly and unpredictably. Therefore, this study recommends that hotel managers should continue to closely monitor the external environment and any emerging developments to be fully responsive. Furthermore, in accordance with the changes in the environment, managers should revise performance measures and include new measures (e.g. postcrisis measures and specific health and safety measures) in the BSC in a timely manner to align the system with the strategy of the hotel (Sainaghi et al., 2017). For example, many hotels have faced staffing problems due to the pandemic, and managers now urgently need to incorporate up-to-date performance indicators in their BSC to ensure that they collect relevant information and follow up on this issue. Obtaining such information through the BSC is critical for hotels’ quick recovery. These issues underline the importance of more frequent performance reviews to minimise the impacts of any crisis on hotels. Senior management should pay critical attention and constantly scan the environment—both internally and externally—for potential issues to manage any future crisis and turn it into a strategic success. Finally, considering COVID-19 has drastically challenged the hotel industry’s operations, hotel managers should develop innovative approaches to their products and services and integrate them into their PMS to ensure that they follow up their progress in their adaptation to changing environmental conditions and customer preferences.

The results of this study are subject to several limitations. First, the study only included four- and five-star hotels in Turkey, meaning the outcomes cannot be considered conclusive. Conducting future studies in other countries and settings might reveal different results due to structural differences in management and different external environmental effects, such as the differing impacts of COVID-19 in different countries. Second, the questions were based on the perceptions of the respondents, although this type of research is generally conducted using this method. A further limitation is related to the response rate. At the time the data were collected, the global COVID-19 pandemic had led to the closure of many hotels, creating an obstacle to data collection. In addition, a longitudinal study could enhance the understanding of this subject over time and provide more accurate results. Therefore, longitudinal studies can be developed in the future, considering the beginning of the pandemic. Taking into account that the impact of COVID-19 continues to reshape the hotel industry, future studies could consider the frequency of measuring performance to assess organisational progress during difficult times. Finally, although the relationships described in Figure 1 are comprehensive, no study can be regarded as fully exhaustive; thus, the framework should not be regarded as such. Future studies could include other contextual factors, such as advanced service technology, to extend this study’s model with the aim of obtaining additional insights.