An empirical study of the use and usefulness of financial, non-financial …library.imtdubai.ac.ae/Faculty Publication/Dr.rajesh... · · 2013-01-08140 Int. J. Managerial and Financial

140 Int. J. Managerial and Financial Accounting, Vol. 3, No. 2, 2011

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An empirical study of the use and usefulness of financial, non-financial and subjective measures for performance evaluation in industrial companies in Bahrain

P.L. Joshi* University of Bahrain, Box 32038, Bahrain E-mail: [email protected] *Corresponding author

Rajesh Kumar Institute of Management Technology, Dubai, UAE E-mail: [email protected]

Jasim Al-Ajmi University of Bahrain, Box 32038, Bahrain E-mail: [email protected]

Abstract: This study uses survey data from 47 industrial companies located in the Kingdom of Bahrain in order to examine to the extent to which the companies combine the use of financial, non-financial and subjective measures in evaluating their performance. The survey reports that, although ROI is the most popular financial measure, industrial companies use an integration of financial and non-financial measures. Firm size also influences the use of these measures and significant differences were observed among the large and medium size firms with respect to operations-related measures. With the exception of ROI in a few cases, the use of performance measures was not found to be significantly different between industries. However, significant differences are found in the use of measures, particularly in financial and non-financial measures, when the data is analysed by line of business (by number of divisions). Furthermore, the study indicates that the various types of measures have different impacts on important employee actions, such as ‘contribute to the quality of the short-term operational decisions’, ‘contribute to the quality of the long-term strategic decisions’, ‘encourage gamesmanship or manipulation’, ‘encourage innovation’ and ‘provide focus on the goals of the departments in the firm’.

Keywords: balanced scorecard; BSC; financial measures; non-financial measures; subjective measures; Bahrain; industrial companies; size.

An empirical study of the use and usefulness of financial 141

Reference to this paper should be made as follows: Joshi, P.L., Kumar, R. and Al-Ajmi, J. (2011) ‘An empirical study of the use and usefulness of financial, non-financial and subjective measures for performance evaluation in industrial companies in Bahrain’, Int. J. Managerial and Financial Accounting, Vol. 3, No. 2, pp.140–169.

Biographical notes: Prem Lal Joshi is a Senior Professor at the University of Bahrain. He has taught in India, Kenya, Turkey and Bahrain. He has presented papers in more than 33 international conferences and has published over 60 research papers in leading international and regional journals. He has also conducted several researches in inter-disciplinary areas. He has authored five books. He is also the Editor-in-Chief of two international journals in Accounting. He is on the editorial board of several journals

B Rajesh Kumar is an Assistant Professor of Finance at the Institute of Management Technology, Dubai. He received his PhD from Indian Institute of Technology (IIT Kharagpur). His publications have appeared in Afro Asian Journal of Finance and Accounting, Journal of Applied Business and Economics, IIMA Vikalpa, IIMB Management Review, IIMC Decision etc. He has authored two books including a text book on mergers and acquisitions published by Mc GrawHill Higher Education.

Jasim Al-Ajmi is a Professor of Finance at the University of Bahrain. He has worked in the banking industry and has published extensively in the areas of corporate governance, financial institutions, investors’ behaviour, capital markets, risk management, financial analysis, and Islamic finance. He is a Board Member of the Eskan (Housing) Bank, Chairman of the remuneration committee of the Eskan Bank, and a member of the audit committee of the Eskan Bank.

1 Introduction

In view of the transformation taking place in manufacturing companies around the world, performance measures have been generating a lot of discussion, with strong arguments that traditional, financially focused systems can be damaging, because the current business environment demands more accurate and different measures of performance, not just a historical perspective on cost driven performance measures (Carr and Hassan, 2008). In developing countries like Bahrain, organisations are recognising the importance of having both qualitative and quantitative information in the formulation and support of their strategies. The present study aims to contribute to building an understanding of the trend of combining financial, non-financial and subjective measures in the performance evaluation of industrial companies in Bahrain. Bahrain, as a developing country, has been undergoing a process of modernisation of its manufacturing operations in order to meet ever growing competition. Therefore, even in a developing country like Bahrain, all business functions have to adapt to the changed business environment and adopt changing performance measurement systems.

142 P.L. Joshi et al.

2 Literature review

Previous studies have dealt with how managers judge performance measures they have been using (e.g., Banker et al., 2004; Dilla and Steinbart, 2005; Ittner and Larcker, 2003). Other studies suggest that modern performance measurement systems place less significance on financial measures. However, it is still important to link performance measures with financial measures. There is a growing literature on the use of non-financial measures in the Western world. For example, in the UK, Bhimani (1994) and Dugdale (1994) reported that companies were quite receptive to the use of non-financial measures. According to Pierce and O’Dea (1998), over 50% of respondents in Ireland reported the use of non-financial measures either very frequently or often. Similarly, Ittner and Larcker (2003, p.95) studied implementation issues for non-financial performance measures, and they concluded that “they have become a shabby substitute for financial performance” and “they will offer little guidance unless the process for choosing and analysing them comes to rely less on generic performance measurement frameworks and managerial guesswork and more on sophisticated quantitative and qualitative inquiries into the factors actually contributing to economic results”.

It has been argued that measurement systems have to be comprehensive because performance in many jobs involves multiple activities. For example, Hitt et al. (2005) state that if only some aspects of performance are measured, the results can be misleading, and can skew the data that are used for taking action to improve performance. Therefore, there has been a move away from the traditional approach to performance measurement. The traditional approach emphasised the use of financial measures to evaluate a business unit’s performance, while a more recent approach also considers non-financial measures. Since the present business environment is characterised by increased customisation, flexibility, responsiveness, and associated advances in manufacturing practices, non-financial performance measures are needed to augment financial performance (Kaplan and Norton, 2001; Van der Stede et al., 2006). In addition, a number of scholars have argued that broadening the set of performance measures would enhance organisational performance because managers have an incentive to concentrate on activities for which their performance is measured and this often involves the sacrifice of relevant but unmeasured activities (Hopwood, 1974). In this context, Baiman and Rajan (1995) identified the potential benefit of subjective performance measures, including mitigating distortions in managerial effort by removing dysfunctional behaviour induced by objective performance measures. In addition, subjective performance measures also reduce noise in the overall performance evaluation in that they are influenced by uncertain, uncontrollable events.

Kaplan and Norton (1992, 1993, 1996a, 1996b, 2001a, 2001b, 2001c, 2004) and Kaplan (2006) developed the balanced scorecard (BSC) as a strategy implementation and control model. The BSC is a key element of a strategic management system that requires organisations to translate strategic goals into financial and non-financial performance measures for monitoring strategy implementation and updating strategy, using a strategic learning loop. The BSC model has evolved and a strategy map can be used to visualise these strategic linkages (Kaplan and Norton, 2001b). Ittner and Larcker (2001) view the BSC as a major development in management accounting, and they addressed several implementation issues (Ittner and Larcker, 1998, 2003). The BSC has been characterised as a control system which is based on top-down hierarchical measurements and criticised


for not being rooted in a dynamic environment or in the organisation (Nørreklit, 2000, 2003).

Sim and Koh (2001) use information collected from 83 electronics companies located within the USA, and results from the study provide support for the use of finance and non-financial measures. Specifically, the findings show that manufacturing plants that have strategically linked their corporate goals or objectives to their performance measurement systems, via the scorecard, performed better than those that did not. Only 8% of companies surveyed in Caribbean countries used the BSC (Forde et al., 2006). Similarly, Gomes et al. (2007) report the increasing significance of non-financial and non-traditional performance measures in an information flow between executives and financial analysts in the context of manufacturing performance measurement and evaluation. The Appendix contains a comprehensive list of studies on the use of financial and non-financial measures.

Despite the trend towards the integrated use of financial and non-financial measures of performance, a comprehensive study carried out by Gosselin (2005) in Canada found that financial measures are more frequently used by manufacturing firms, while few companies have implemented BSC. Chow and Van Der Stede (2006), in a sample of 128 companies, also found companies still favour financial measures over non-financial measures. In a survey by Aggrawal and Gupta (2006) of automobile and consumer electronics companies in India, they found that financial performance is given the largest importance by companies. Therefore, in the context of industrial companies in Bahrain, we may expect a similar trend and practice because of the traditional cultural dimensions of Arabian culture.

H1 Industrial firms in Bahrain do not have high a tendency to use more financial measures than non-financial measures.

In the literature, it is argued that larger firms are more diverse and decentralised and they have the practice of using a more administratively-oriented control systems and budgetary sophistication (e.g., Merchant, 1981). In the context of BSC, a study by Hoque and James (2000) reported that large size is positively associated with the overall use of BSC measures. But, in another study, Hoque et al. (2001) indicates that business unit size appears not to be an important predictor of a performance measurement system using the BSC. Speckbacher et al. (2003) investigated the impact of size on BSC use and found that there is a significant association between size and BSC usage. Furthermore, Chow and Haddad (1997), Gumbus and Lussier (2006) and Philips et al. (2003) emphasised that that there is a need for BSC to be used by small and medium enterprises (SMEs). Therefore, we formulate the following hypothesis:

H2 There are no significant differences in the use of financial and non-financial measures by large and medium sized companies in Bahrain.

Large and complex organisations that deal with, and are accountable to, an increased number of stakeholders are likely to use more comprehensive measurement systems that enable them to measure multiple dimensions of organisational performance, including both financial and non-financial measures (Hoque and James, 2000).

Small and medium organisations are likely to place greater emphasis on financial measures in their performance measurement system (Neely et al., 1995, 1996). SMEs do not face the same degree of pressure as large organisations to meet the requirements and expectations of different stakeholder groups. Financial measures are also likely to be


more appealing to entrepreneurs and managers of SMEs because they are available at a minimum cost and effort, generally relying on information which is readily available from their financial accounting system (Hvolby and Thorstenson, 2001). In addition, SMEs have less need to develop and implement multi-dimensional measurement systems because managers of such organisations are often able to oversee operational activities of the organisation by themselves and take the necessary actions. A study by Perera and Baker (2007) shows that SMEs place a significantly greater reliance on financial measures of firm performance.

3 Research objectives and methodology

The aim of this study is to determine the current state of use of financial and non-financial measures in performance evaluation by industrial companies in Bahrain. The survey was designed to extend the literature on the use of performance evaluation measures by studying a different cultural environment. The specific objectives are to:

1 investigate the extent to which industrial companies in Bahrain use a combination of financial and non-financial and subjective measures in their performance evaluation

2 analyse the characteristics of users, to determine whether the practices differ between companies by size, industry and line of business (number of divisions).

The sample of companies selected for this study was extracted from the website of the Ministry of Commerce and Industry, Bahrain (http://www.industry.gov.bh/english/). We excluded from our sample firms with sole proprietorship. On a random basis, 176 companies were contacted by telephone and asked whether they would participate in our questionnaire study. A total of 106 firms requested the questionnaire. A six page questionnaire, with a covering letter, was personally distributed by the students of ACC 491: current issues in accounting, to the CEO’s office, the Head of Accounts and Finance, or, in some cases, also to public relations managers, with a request that the questionnaire be made available for collection in person, or faxed to the researchers, when complete. The survey was conducted during October and November 2009.

The questionnaire was constructed using items taken from previous studies (e.g., Jusoh, 2008; Ismail, 2007; Chow and Van Der Stede, 2006; Watkins, 2003). Pilot tests were conducted with two companies in Bahrain and, based on the feedback, the questionnaire was revised. The questionnaire comprised two parts. Part A consisted of a number of questions about the general characteristics of the respondents, such as type of industry, position, experience, number of employees, total assets, foreign operations, number of divisions, etc. For Part B of the questionnaire, organisations had to indicate the extent to which they use 48 performance measures relating to financial, operations, customer, employee and subjective measure. A five point Likert-type rating scale was used.

A total of 57 questionnaires were returned making a response rate of 32.4%. However, ten questionnaires were found to be incomplete, and they were excluded from the final list for analysis. Therefore 47 questionnaires were found to be usable. The respondents represented several industries, including aluminium, petrochemicals and plastics, engineering, metal and metal work, food processing, pharmaceuticals, chemicals, and construction. Information about the respondents’ characteristics is presented in Table 1.


Table 1 Respondents’ demographic characteristics

Characteristics of respondents N Percentage 1 Respondent’s position: Accounting 21 56.8 Non-accounting 16 43.2 Total 37 100.0 2 Nationality of respondents: Bahraini 25 55.6 Expatriates 20 44.4 Total 45 100.0 3 Total experience of respondents: Less than 5 years 6 13.3 5–10 years 11 24.4 10 and more years 28 62.3 Total 45 100.0 4 Auditors: Big 4 18 47.4 Non-Big 4 20 52.6 Total 38 100.0 5 Number of employees: Less than 50 13 27.7 50–100 4 8.5 100 and more 30 63.8 Total 47 100.0 6 Total assets (in BD) Less than BD 5 m 18 38.3 5–10 11 23.4 10–20 3 6.4 20 and more 15 31.9 Total 47 100.0 7 Number of divisions: Less than 3 16 35.6 3–6 14 31.1 6 and more 15 33.3 Total 45 100.0 8 Export by respondents’ companies: Yes 28 59.6 No 19 40.4 Total 47 100.0


4 Results and discussion

One of the most common problems cited with survey methodology is non-response bias. In line with the recommendations of Oppenheim (1992) and Wallace and Mellor (1988), the first 15 questionnaires were compared with the last 15 questionnaires, using a t-test to investigate the differences. The result showed no significant difference between the 15 early and the 15 late responses, implying the absence of non-response bias in the sample. Possible implications are discussed below.

Table 1 presents information on the respondents’ characteristics. Respondents came from the areas of accounting (56.8%) and from non-accounting areas (44.4%). The non-accounting respondents were production managers/supervisors. The experience and current positions indicate that respondents would have a collective financial orientation and perspective on issues relating to the use of financial and non-financial measures in their respective organisations.

In order to assess the internal consistency of responses, a reliability test was performed on the questionnaire responses. Table 2 Reliability test of internal consistency in the responses

Financial, non-financial and subjective measures Cronbach alpha coefficient

1 Financial-related measures 0.88 2 Production-related measures 0.86 3 Employee-related measures 0.77 4 Customer-related measures 0.56 5 Subjective-related measures 0.86

Table 2 reveals that the Cronbach coefficient values are over 0.70 for financial, production, subjective and employee related measures. Only for customer related measures was the value well below the accepted level of 0.60. These values clearly indicate the internal reliability of the questionnaire design and responses. Descriptive statistics for each measure is presented in Table 3.

Table 3 shows that all the evaluation measures which received scores above the mean of the scale are considered important in the evaluation process.

The most important financial measure used for performance measurement by industrial companies in Bahrain is ROI (mean = 3.85). This finding is in line with Ismail (2007) whose study in Egypt reported that profit margin was the most commonly used measure by companies in Egypt. Other measures used by companies are gross and unit contribution margins. This study supports prior research that financial measures are most frequently used by manufacturing companies (e.g., Jusoh, 2008; Chow and Van Der Stede, 2006; Gosselin, 2005).

On the other hand, companies use production volume, machine productivity and labour productivity, material usage and capacity utilisation as operation-related performance measures. The findings indicate an increasing level of modernisation and an emphasis on increasing productivity in operations. This is in line with the findings of other studies which found that companies accord the greatest importance to operations strategy and use non-financial measures to improve their operations (Chow and Van Der Stede, 2007; Gosselin, 2005; Sharma, 2003).


Table 3 Use of financial, non-financial and subjective measures by industrial companies in Bahrain


Table 3 Use of financial, non-financial and subjective measures by industrial companies in Bahrain (continued)






For employee-related measures, companies consider the safety of employees among the most important measures, and gave it the highest mean score (mean = 4.33). Other measures they use are employees’ skills, employee training and employee satisfaction, and employee empowerment. It should be noted that for the last decade the government’s emphasis in Bahrain has been on improving the skill levels of local people, for which several training and on the job schemes have been started. The objective is to gradually replace expatriates by locals in order to speed up the process of Bahrainisation.

Progressive industrial companies have been paying the utmost priority to customer care and services. Companies in Bahrain are no exception to this. Our study reveals that customer satisfaction is considered the most important measure by the respondents as it received the highest mean score (mean = 4.21). Again this finding is consistent with Ismail (2007) who, in the Egyptian context, found customer satisfaction was the most commonly used non-financial measure of performance evaluation.

Other measures utilised by them include: delivery performance, time to respond to customers’ problems and time to fill customers’ orders. These are all related to improving internal business processes within the framework of Kaplan and Norton’s theory. The results clearly indicate that industrial companies are fully aware of the importance of customer sentiment, understand it and take serious action to improve it.

Furthermore, companies also combine the use of subjective measures, as these measures received some of the highest mean scores. The results show that companies in Bahrain strongly believe in willingness to share knowledge within the organisation as this measure received a high score (mean = 4.26). Other subjective measure which are considered important in performance evaluation are ‘my cooperation with other departments within the organisation’, ‘my loyalty toward the firm’ and ‘my ability to effectively acquire new skills/knowledge’. These results show that industrial companies in Bahrain emphasise improving the human quality and relationships at work in order to achieve higher productivity.

The overall means for operational, customer, employee and subjective measures are higher than the overall mean for financial measures. Industrial companies in Bahrain have a greater tendency to use non-financial measures than financial measures alone. A pairwise comparison between financial and non-financial measures also shows significant differences with respect to several measures. This analysis supports the emerging evidence that companies increasingly use a balanced mix of financial, non-financial and subjective measures in their performance evaluation policy. Therefore, we reject the null hypothesis that industrial companies in Bahrain have a tendency to use financial measures more than non-financial measures.

To find out which characteristics of the industrial firms explain the adoption of these performance measures, we analysed the data by size (total assets), by line of business (number of divisions), by foreign operations and sensitivity to environmental issues. As no significant differences were identified when data was analysed by foreign operations and by environmental sensitivity, these results are not reported here.

4.1 Size effect

The results analysed in terms of the size of the companies are presented in Table 4. Using the median value of total assets, the firms are divided into medium and large enterprises. Firms having an asset value of less than BD20 million are considered medium and of BD20 million or more as large.


Table 4 Firms size (total assets), line of business and the use of performance measures


Table 4 Firms size (total assets), line of business and the use of performance measures (continued)






Table 4 shows that when data is analysed by total assets as the size indicator, most of the significant differences are found with respect to operation-related measures. However, in the case of financial measures, the only difference is found with respect to maintenance expenditure (t = 2.04 df = 44 p < 0.05). The mean value for larger firms is higher than for medium sized firms. One plausible explanation for this difference may be the age of the technology used by industrial firms in Bahrain. It would need a huge amount of investment for larger firms to modernise their plants compared to small and medium size firms. Another reason could be the efficiency of the plants of these industrial firms in terms of production yield.

Furthermore, significant differences are observed for eight operations-related measures. These are: material usage (t = 2.52; df = 45; p < 0.01), capacity utilisation (t = 2.73; df = 44; p < 0.01), setup efficiency (t = 2.15; df = 43; p < 0.05), inventory levels (t = 2.21; df = 45; p < 0.05), number of warranty claims (t = 2.40; df = 45; p < 0.05),and product defects (t = 2.27; df = 44 p < 0.05). Also, significant difference is found at the 0.10 level for labor productivity and scrap as a percentage of production. The mean values for larger firms are higher than for medium size firms.

An interesting feature of the findings relates to the employee-related measure for employee absenteeism (t = 3.33; df = 4; p < 0.01). The mean score is higher for medium sized firms than larger firms. The explanation for this difference may be that, in large organisations, it appears that supervision is more rigorous and controlled. When we contacted some of the large firms, we found that the majority have strict rules for late-coming and absence from work. For example, if the employees are late or absent from their work, their wages or salary are cut proportionately.

The only statistical difference found with respect to customer-related measures between large and medium sized firms is for number of customers returns (t = 2.30; df = 44;p < 0.05). Again the mean value is higher for medium sized (mean = 3.53) than for larger firms (mean = 3.02). This may be an indication of the product quality and customer relations management (CRM). CRM for larger firms may be more effective than in medium sized firms.

Lastly, for subjective-related measures, significant difference is observed at the 0.10 level for employee spirit/morale. The mean value is higher for larger firms. It may be that larger firms in Bahrain generally offer good salary packages, better safety measures and favourable working conditions as they have more resources and better governance practices. Long working hours and the fear of job losses during the recession could be other reasons for this difference.

Thus we reject the null hypothesis. It appears that as size increases, firms seem to be involved in more complex operations, and therefore need performance measures which are more non-financial, broader, comprehensive and multiple. This explains why firm size is an important factor for using financial and non-financial measures. This finding seems to be consistent with previous studies by Speckbacher et al. (2003) and also with other similar studies with respect to the effect of size on accounting and budgetary control practices (Ezzamel, 1990; Merchant, 1981).

4.2 By industry

Data was also analysed by industry. However, a significant difference was observed for only one financial measure. ROI was found to be significantly different across industries


(F = 2.98; df = 5, 40; p,0.05). The reasons could be the level of competition and the characteristics of each industry segment, including their different cost structures.

In the case of operation-related measures significant differences were observed for percentage of on-time production (F = 2.46; df = 5, 40; p < 0.05), and manufacturing cycle time (F = 2.13; df = 5, 40; p < 0.10). Similarly, among customer-related measures, customer retention (F = 2.13; df = 5, 40; p < 0.10) was significantly different in different industries.

It should be stressed that, although some variations are observed across industry types, no definite conclusion was made concerning the effect of industry type on emphasis and use of non-financial measures.

4.3 By line of business (number of divisions)

ANOVA is used to analyse data by line of business (number of divisions). Significant differences are observed for seven measures with respect to operations-related measures. These are: machine productivity (F = 3.01; df (2, 42); p < 0.10), material usage (F = 8.43; df (2, 42); p < 0.01), setup efficiency (F = 5.42; df (2, 40); p < 0.01), capacity utilisation (F = 4.87; df (41, 2); p < 0.05), scrap (F = 3.49; df (41, 2); warranty (F = 3.38; df (2, 42); p < 0.05), and design (F = 6.15; df (41, 2); p < 0.01). Similarly, absenteeism, among employee-related measures, and ‘My cooperation with other departments within the organisation, among subjective-related measures, were found to be significantly different between lines of business. On the other hand, a significant difference was found for financial-related measures with respect to material variance and overheads. This shows that when the number of divisions increases, the material costs and overheads differ because of the type of products the firm produces. Since the divisions of a company may be characterised by different quality of information systems, corporate environmental integration, product innovation, and product quality, the efficacy of these factors may be more effectively assessed by evaluating their impact on performance measured in non-financial terms (Dunk, 2005).

4.4 Selected attributes and consequences of financial, non-financial and subjective performance measures

In order to find how the financial, non-financial and subjective measures may impact on other aspects of the industrial firms performance, the respondents were asked to estimate the influence of different measures. The responses were measured using a Likert scale, where five indicated a very great extent and one indicated not at all. Furthermore, we applied a paired t test to analyse the responses in order to see the statistical difference between financial and non-financial measures, financial and subjective measures, and non-financial and subjective measures. The results are presented in Table 5.


Table 5 Mean ratings and significant differences of the selected attributes N = 47


It is clear from Table 5 that financial measures contribute to the quality of the long term decisions the firm makes (mean = 3.85), provide focus on the goals of the department (mean 3.80), encourage a short term focus on the business (mean 3.74), and encourage innovation (mean 3.70).

Non-financial measures provide focus on the goals of the department (mean 3.89), encourage innovation (mean 3.74), encourage a short term focus on the business (mean = 3.65), and encourage alignment of objectives across departments (mean = 3.59). Similarly, subjective measures encourage a short term focus on the business (mean = 3.62), provide focus on the goals of the department (mean 3.54), contribute to the quality of the long term strategic decisions the firm makes (mean = 3.52) and encourage alignment of objectives across departments (mean = 3.52).

Furthermore, significant differences across the average ratings of different types of measures were calculated based on t-tests at a 10% two-tailed probability level using paired t tests. It was found that there is a significant difference for at least one comparison per measurement attribute. Paired t tests between financial and non-finance measures show significant difference with respect to ‘contribute to the quality of the short-term operational decisions you make’ (t = 1.848; df = 44; p < 0.10), and ‘contribute to the quality of the long-term strategic decisions’ (t = 2.403, df = 45; p < 0.01).

On the other hand, when financial and subjective measures are compared, we observe some differences with respect to ‘encourage gamesmanship or manipulations’ (t = 1.713, df = 44, p < 0.10) and ‘contribute to the quality of the short-term operational decisions you make’ (t = 1.886, df = 45, p < 0.10). Thus, subjective measures are seen by the respondents as more effective in curtailing short-term operational decisions and gamesmanship. These differences are in line with the findings of Chow and Van Der Stede (2006) and with popular belief as expressed in the literature.

Similarly, when results are compared for non-financial measures with subjective measures, we find statistically significant differences with respect to ‘encourage innovation’ (t = 2.286, df = 45, p < 0.01), and with respect to ‘provides focus on the goals of your department’ (t = 1.955, df = 45, p < 0.10). The respondents see non-financial measures and subjective measures as the greatest encouragement for innovation and focusing on departmental goals.

On the other hand, non-financial measures are not seen as significantly different from financial measures in their contribution to operational and strategic decision making and their capacity to align intra and interdepartmental objectives. One conclusion from the results is that subjective measures are seen to be the least effective among the three measurement types along these dimensions. The reasons could be that industrial firms in Bahrain may be still placing greater weight on financial measures in their performance evaluation.

5 Conclusions and implications

This study focuses the extent to which industrial companies in Bahrain combine the use of financial and quantitative and qualitative measures in their evaluation of organisational performance. Therefore, this study sought to advance our knowledge and understanding of performance evaluation practices from a different cultural context in a developing country.


It has frequently been claimed in the literature that non-financial measures are superior to traditional financial measures, but these claims should be treated with caution. However, the use of non-financial measures by companies around the world has been increasing. The best policy is to choose the optimal combination of measures of various types in order to achieve the effective measurement of outcomes. Our findings provide important conclusions that managers and accountants from industrial companies in Bahrain have been selecting, implementing and integrating the use of appropriate measures. It appears that they understand that the chosen measures are an integral part of reporting and performance evaluation because they affect employee behaviour, customer services and organisational performance. Furthermore, different measures may have their own strengths and weaknesses, but different types of measures appear to complement each other. The objective is to enhance the quality of performance. Our findings may be used to stimulate both managers and accountants in the use of these measures. However, whether organisations have got the right balance performance measures is something which they may get a better feel of based on their experience over a period of time.

As anticipated, the size of firms also affects the selection of financial and non-financial measures. This explains why firm size is an important factor for implementing the BSC. Similarly, the line of business (number of divisions) may also influence industrial companies in the selection of performance measures, as we observed significant differences between financial and non-financial measures.

One area which calls for further research is how to identify the combination of measures best suited for decision making and what are the best performance measures in a specific industry, as the technology, processes and constraints differ between various industries.

6 Limitations of the study

It was decided to use random sampling from the list of companies on the website of the Ministry of Commerce and Industry, so long as the complete address or telephone number of the company was available. Only those industrial companies whose address or telephone number was available were chosen. Another possible limitation of a questionnaire for this type of survey is the possible misunderstanding of the measures used and inconsistencies introduced by that misunderstanding.

The sampling design of this study restricts generalisation, in that it cannot be claimed that the sample is representative of all industrial companies in Bahrain. Also a relatively low response rates must be taken into account.

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coreca d_Adopters_and_Non.doc


Appendix

Summary of prior studies

Study Objectives Methodology Sample and period Results

341 firm Net income has no ability to explain the market value for the pooled sample or for any of the internet sectors examined. Page views have the greatest explanatory power for e-tailers and content/community firms.

Graham et al. (2002)

This study assesses the extent to which non-financial measures of internet usage are incrementally value-relevant over and above basic financial information across four internet industry sector

Regression analysis Q1 1999–Q1 2000

For service companies, unique users have the greatest ability to explain market values

35 airlines – 246 firm year

observation.

Antonio and Venkatachalam (2004)

This paper investigates the role of non-financial performance measures in executive compensation in Airline Industry.

Regression analysis

1986–2000

Passenger load factor is an important non-financial measure for the industry which is positively related to CEO cash compensation. Firms with powerful CEOs and high levels of stock return volatility place more weight on passenger load factor in determining CEO compensation.

86 manufacturing SME.

Sujatha and Baker (2007)

This study examines the use of financial and non-financial performance measures in small and medium size manufacturing enterprises (SMEs) in Australia.

Two sample t-tests, regression, chi square test

2004

SMEs place a greater reliance on financial measures of performance, although with increase in size there is a tendency to make more use of non-financial measures.


Summary of prior studies (continued)

Study Objectives Methodology Sample and period Results

317 firms Ittener et al. (1997)

This paper examines the factors influencing the relative weights placed on financial and non-financial performance measures in CEO bonus contracts.

Regression 1993–1994

The study finds that the use of non-financial measures increases with the level of regulation, the extent to which the firm follows an innovation oriented strategy, the adoption of strategic quality initiatives and the noise in financial measures

Study Details

Hudson et al. (2001)

Outline a number of characteristics that differentiate SMEs from larger businesses including personalised management, little devolution of authority; severe resource limitations in terms of management and manpower as well as finance; reliance on a small number of customers, and operating in limited markets; flat, flexible structures; high innovatory potential; reactive, firefighting mentality; and informal, dynamic strategies.

Hayes and Schaefer (2005)

The study explores how firms use ‘individual’ or ‘non-financial’ measures of performance in executive compensation contracts. The study models a firm that conditions bonus payments to executives on information that is not available to those outside the firm. The main result is that increases in corporate myopia can, under some conditions, lead to increased profits.

Bushman et al. (1996)

Use survey responses and proxy disclosures, respectively, to study how managerial pay depends on individual-based or non-financial performance measures that may not be available to those outside the firm.

Aggrawal and Gupta (2006)

Carry out a survey of all companies in India in the product category of automobiles and consumer electronics. Results indicate that financial performance is given the largest importance, followed by competitive market performance. Innovation, however, seems to be ignored.

Everette et al. (2001)

The paper analyses the quality improvement practices and the effect on manufacturing firm performance in the USA and Mexico. For 345 firms multiple quality improvement variables are correlated with seven quality measures, four financial measures, and one operating performance measure.

Hand (2000) Examines the value-relevance of basic accounting data for Internet companies using a log-linear model and finds that the data is highly value-relevant. When earnings are decomposed into revenues and expenses, revenues are weakly value-relevant and research and development (R&D) and marketing expenditures are priced as if they are intangible assets.

Trueman et al. (2000)

The study finds that there is no significant relationship between earnings and market value in the case of Internet companies. The study finds that unique visitors and page views exhibit incremental explanatory power for stock prices over and above the financial measures examined. Furthermore, their results indicate that relative to unique visitors, page views have a far greater incremental explanatory power for Internet firms classified as e-tailers.



Study Details

Rajgopal et al. (2000)

The study finds that web traffic as measured by unique visitors and reach is highly value-relevant after controlling for book value and earnings. There is no significant relationship between traffic and revenue, and revenue growth. The study finds the web traffic to be an important value-driver for access providers, content providers and portals, but not for companies that sell domain names, security services, network infrastructure or software.

Amir and Lev (1996)

On a stand-alone basis, traditional financial statement information is largely irrelevant for the wireless communications industry. Non-financial indicators such as population size and market penetration are highly value-relevant.

Behn and Riley (1999)

In the Airline industry, the non-financial data has the potential to enhance one’s ability to predict financial performance as measured by quarterly revenues, expenses, and operating income. The passenger load factor has implications beyond traditional accounting measures for assessing firm performance and equity valuation.

Banker et al. (2000)

Firms are increasingly using non-financial performance measures such as customer satisfaction and product quality in the contracting process within firms. The reason for the use of non-financial measures in compensation contracts is that they provide information incremental to accounting measures in rewarding and motivating managers.

Banker and Datar (1989)

Accounting performance measures do not capture all the dimensions of CEO performance.

Bushman and Indjejikian (1993) Kim and Suh (1993) Feltham and Wu (1999)

This study finds that stock price is an inefficient aggregator of publicly available information and suggests that the role for other performance measures emerge in contracting.

Rajgopal et al. (2003)

Stock prices do not efficiently incorporate the implications of non-financial measures.

Ittner and Larcker (1998)

The study finds a positive relationship between company value and non-financial measures of customer satisfaction.

Hughes (2000) Non-financial measure of pollution is highly value relevant for electric utilities with high pollution levels.

Hirschey et al. (1998)

Investigates the extent to which non-financial information on the quality of inventive output for high-tech companies is value-relevant. The authors find that while financial information is highly relevant for security valuation in the high-tech sector, non-financial indicators of inventive output (patent data) can be useful in enabling investors better appreciate the long-term benefits.

Meyer (1998) Non-financial indicators serve as leading, and financial as lagging, indicators Szymaski and Henard (2001) and Dick and Basu (1994)

Non-financial measures such as customer satisfaction, customer loyalty, and brand equity have attracted the attention of many managers.



Study Details

Clark (1999) The study tracing the history of marketing performance measures, showed that traditional financial measures (profit, sales, cash flow) had expanded to a range of non-financial (such as market share, quality, customer satisfaction, loyalty, brand equity), input (such as marketing audit, implementation) and output (marketing audit, efficiency/effectiveness) measures.

Ambler and Kokkinaki (1997)

The study, through the survey of five leading marketing journals, finds 19 different marketing measures of success. The most recurrent among which were sales, market share, profit contribution and purchase intention

Ong and Shaw (2007)

The study suggests that financial measures is still popular among most of the companies because non-financial measures such as customer satisfactions, quality, market share and human resources, tend to be subordinated to financial figures.

Eccles (1991) Senior managers in large high-tech and smaller manufacturing organisations had recently taken direct responsibility for adding non-financial measures such as customer satisfaction, quality, market share, human resources, manufacturing effectiveness and innovation to their existing performance measurement systems.

Wiersma et al (2008)

Test the relative and incremental information content of two non-financial performance measures compared to financial performance measures for future financial performance. The results show that the two non-financial measures absence frequency and on-time delivery do not have more relative information content than lagged financial measures.

Ahmed et al. (2005)

The paper reports on a large scale, empirical investigation of the measurement practices in British factories at the beginning of the 21st century. Various partial relationships are found, and ‘across the board’ high levels of shop-floor performance measurement are found to be associated with a severely competitive environment, an upward communication corporate ethos, and with the adoption of JIT or TQM/TPM

Vaivio (1999) This paper explores the emergence of non-financial measures in an organisational context of Lever Industrial-UK, a service oriented British chemicals company. The paper points to the systematisation of non-financial measures as an essential phase of the change process.

Butler et al. (1997)

This article reports on a study undertaken for Rexam Custom Europe to determine, develop and implement a ‘balanced scorecard’ for top-level use. This article briefly reviews the theoretical background through the development of integrated performance measures, describes the performance measures currently in use at Rexam Custom Europe and the proposed measures based on a two-part balanced scorecard tailored to suit the particular requirements of the company.

Bungay and Goold (1991)

The study suggests that strategic controls can be considered to be non-financial performance measures and they are of particular value in a diversified company in controlling, monitoring and guiding the development of operating units.



Study Details

Hoque (2004) Based on survey data of 52 manufacturing companies, the results reveal the existence of a significant and positive association between management’s strategic choice and performance acting through management’s high use of non-financial measures for performance evaluation. On the other hand, the study found no evidence of a significant relationship between environmental uncertainty and performance through management’s use of non-financial performance measures.

Venkatachalam and Antonio (2001)

Using a sample of Internet firms the study documents that web traffic is an important non-financial measure for firms in the Internet industry and is positively associated with CEO total compensation and total change in CEO wealth.

Egyptian study(2007)

This study aims to examine performance evaluation measures across 50 private sector companies in an Egyptian context. Companies rely on both financial and non-financial measures of performance evaluation. The profit margin, as a financial measure, is also the most commonly used performance measure. Customer satisfaction is the most commonly used non-financial measure of performance evaluation.

Ramanan (2002)

This article suggests that an overemphasis on achieving and maintaining short-term financial results can cause companies to overinvest in short-term fixes and to under invest in long-term value creation, particularly in the intangible and intellectual assets that generate future growth.

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