The Impact of Supply Chain Integration Factors on Order Fulfilment in Public Hospitals. Kabossa A.B. Msimangira

Transcription

1 The Impact of Supply Chain Integration Factors on Order Fulfilment in Public Hospitals Kabossa A.B. Msimangira Northern Melbourne Institute of TAFE, Australia 0161 The Asian Business and Management Conference Abstract This study investigates the critical operational factors influencing supply chain integration (SCI) and their impact on order fulfilment in public hospitals. Based on the literature review and with the help of the practitioners we develop a hypothesised model. The results of empirical study are based on the responses from purchasing and supply personnel in New Zealand public hospitals. A survey research approach was used to collect data and multiple regression analysis was used to test the hypotheses. The key findings of this study suggest that SCI operational factors, such as crossfunctional process within the hospital, collaborative planning, forecasting and replenishment, an organisation s strategy that includes supply chain integration, classifying inventories according to their importance, an effort to control costs, have positive influence on order fulfilment. We find lack of willingness to share information and inappropriate information systems are key barriers to effective SCI in the public hospitals. In conclusion, the findings of this study have implications for hospitals implementing or in the process of implementing SCI in order to reduce costs, and for reseachers the SCI model will be useful for further studies. Keywords: Supply chain integration, Supplier relationships, Public hospitals, New Zealand iafor The International Academic Forum 400

2 INTRODUCTION Supply chain integration (SCI) has been considered as a means to reduce operations costs and supply chain ineficiencies, and to improve the service level in an organisation. Lack of integration between members of a supply chain results in operational inefficiencies and hinders the performance of the supply chain (Lambert 2004). Integration is also emphasised by the Supply Chain Council s supply chain operations reference model, that enables users to address, improve, and communicate supply chain management practices within and between all interested parties. It is a process reference model for supply chain management, spanning from the supplier s supplier to the customer s customer (Supply Chain Council 2003). SCM literature has emphasized the importance of SCI in creating value and reducing costs and the cost of logistics in the supply chain (Lee 2000, Lee & Wolfe 2003). Bowersox, Closs and Stank (2000) have classified SCI into six different contexts: customer integration, internal integration, material and service supplier integration, technology and planning integration, measurement integration, and relationship integration. According to Lambert (2004), there are eight key SCM process based approaches that need to be integrated and these are: customer relationship management, customer service management, demand management, order fulfilment, manufacturing flow management, supplier relationships management, product development and commercialization, and returns management. Although there is general understanding on the strategic importance of SCI, little is known regarding the relationship between SCI and its impact on company s business performance (Frohlich & Westbrook 2001). Early SCI research focuses mostly on the management process integration issues related to the manufacturing sector and part of the service sector. Studies of SCM/SCI issues in the health sector are scarce in the literature. For example,task Force Report on Supply Chain Management, a joint initiative of the Ontario Hospital Association of Canada (2001), found that an efficient supply chain could reduce cost; Breen and Crawford (2005) state that e-commerce is an important aspect of SCM; Towill and Christopher (2005) emphasise the use of principles of supply chain design in healthcare; and Okoroh, Gombera and Ilozor (2002) stress that healthcare facilities management is part of the service chain process. Hersch and Pettigrew (2002) emphasise an efficient health care supply chain to improve the quality of care, health service efficiency, and finiancial benefits of organisation. Recently for Australian pharmacetical supply chain, implementation of e-business process in procurement is emphasised to boost efficiency in the supply chain (Bhakoo & Chan 2011). Brennan (1998) advocates SCI in the health care integrated delivery system for better service efficiencies. For New Zealand, Campbell and Sankaran (2005) identify three distinct dimensions of SCI as internal integration, backward or external integration with suppliers, and forward or external integration with customers. However, the study did not identify critical factors influencing the SCI and their impact on order fulfilment. A review of the literature indicates that SCI influences and their impact on order fulfilment in public hospitals are not known. It is evident that there is lack of a model or framework for SCI in the public hospitals, which shows critical operational factors of SCI and their impact on order fulfilment in public hospitals. This paper aims to fill the gap in the literature. The objective of our research is to develop an empirical understanding of the critical operational factors influencing SCI and their impact on order fulfilment. We test the model in the New Zealand public hospital sector and answer the following research questions: 401

3 (i) (ii) What are the critical operational factors influencing supply chain integration in public hospitals? What is the impact of critical supply chain integration operational factors on order fulfilment? This paper is organised as follows: SCI literature review and hypotheses development; research methodology; data analysis and hypothesis testing; results and discussion; and conclusion and further research. LITERATURE REVIEW AND HYPOTHESES DEVELOPMENT Supply Chain Integration in Health Care Supply chain integration is the level to which all activities in an organisation and that of its suppliers, customers, and other supply chain members are integrated (Marquez, Bianchi & Gupta 2004). Cox (2004) argues that SCM is a proactive relationship between a buyer and supplier, and the integration is across the entire chain. Hill and Scudder (2002) emphasise the importance of inter-organisational coordination in the supply chain to integrate activities. Organisations must integrate their operations with trading partners in order to sustain competitive advantage for the whole supply chain (Lambert & Cooper 2000). The literature on SCI is composed of three types of integration: integration with suppliers, integration with customers, and internal integration across supply chain (Frohlich & Westbrook 2002, Frohlich 2002, Narasimhan & kim 2002). SCI is considered a suitable approach for improving business performance in a highly competitive market (Narasimhan & Jayaram 2001). Lack of integration between members of a supply chain results in operational inefficiencies and hinders the performance of the supply chain (Lambert 2004). The operations situation in the health sector regarding SCI lags behind that of manufacturing and other service sectors. Early SCI research has focused mostly on the management process integration issues related to the manufacturing sector and part of the service sector. Little is known concerning how public hospitals can attain SCI. Health care budgets are very tight generally, and that is why health care organisations in all countries are looking for ways to improve the health care supply chain through improving operational efficiencies and reducing costs without affecting quality of patient care. Byrnes (2004, p. 1) states that "25 percent of hospital costs are supply related. The opportunity costs of supply chain inefficiency are enormous. With limited hospital budgets, supply chain inefficiencies consume resources that could be used to make important therapies more available (Byrnes 2004). Hersch and Pettigrew (2002) claim that group purchasing can reduce hospital supply chain expenses by 5% to 15%. Many authors stress on the use of information technology for health care SCI. Novelli (2004, p. 32) provides examples of health care in the U.S., where he finds that information technology is not effectively or routinely applied to the practice of medicine, noting that more than 90% of the 30 billion annual medical transactions are conducted by phone, fax or stamped mail. McGrath and More (2001) stated that poorly integrated information systems, certainly comprise a main problem within the Australian healthcare sector. Their study of a major Australian e-commerce project designed to improve pharmaceutical supply chain efficiency within the healthcare sector revealed that the standards set for the project resulted in improved levels of data and systems 402

4 integration in both within and between organisations (McGrath & More 2001). The importance of integration was also emphasised by Brennan (1998) who suggested that the healthcare organisations should include the complete supply chain in their integrated delivery systems. In addition, Brennan (1998) emphasised that implementation of e-business process in the procurement function might boost efficiency in the supply chain. Research Hypotheses The hypotheses indicated in Figure 1 are exploratory and have not been empirically supported or tested. Armstrong, Brodie, and Parsons (2001) argue that an exploratory hypothesis is the suitable approach to increase knowledge about a phenomenon. SCI Operational Factors and Order Fulfilment The success of an organisation regarding SCI depends on how management critically examines the SCI operational factors, which are likely to affect an organisation s ability to successfully implement SCI. SCI operational factors are concerned with the organisation s activities that can have impact on enhancing SCI in an organisation. Barki and Pinsonneault (2005, p. 165) propose the concept of organisational integration, which is defined as the extent to which distinct and interdependent organisational components constitute a unified whole and they identified two intraorganisational integration: (1) internal-operational (integration of successive stages within the primary process chain (workflow) of an organisation) and (2) internal-functional (integration of administrative or support activities of the process chain of an organisation. Akkermans et al. (2003) found that the executives expected further integration of activities between suppliers and customers across the entire supply. It is important to determine critical operational factors that affect the SCI in an organisation. Hoek and Weken (1998) state that the expected benefits of the increased integration in the inbound and outbound flow of goods are improved responsiveness to customers and increased efficiency in an organisation. The importance of information technology (IT) on operational performance has been emphasized in a study by McAfee (2002), and found that there is a relationship between IT adoption and improvement in operational performance measures (McAfee, 2002). The need to integrate the operations from suppliers to customers has increased tremendously in order to support global operations. Little is known in the literature concerning the influence of SCI critical operational factors on order fulfilment. The nature of critical operational factors can have influence on order fulfilment. Thirumalai and Sinha (2005) revealed in their study of customer satisfaction with order fulfilment in retail supply chains that customers tend to have higher satisfaction levels with order fulfilment. However, the study conducted by Forslund (2006, p. 580) on performance gaps in the dyadic order fulfilment found that customers expectations are not perceived by customers as being fulfilled, customers expectations are over-targeted by suppliers, but suppliers internal performance decreases performance. The study on information sharing and coordination in make to order supply chains conducted by Sahin and Robinson (2005) found that 47.58% cost reduction was achieved as a result of changing from a traditional supply chain to a fully integrated system. In addition, they revealed that although information sharing reduces costs, the major benefit comes from coordinated decision making (Sahin & Robinson, 2005). Furthermore, Petersen and Aase (2004) argue that 403

5 batching of orders produce more savings especially when smaller order sizes are common. However, many researchers, including Bozart and Chapman (1996); Daugherty and Pitman (1995) emphasise that organisations should make their operations more flexible and responsive to their customers requirements and order fulfilment. Hui (2004) argue that strong supply chain integration needs to take into account a firm s resource capabilities and external environments. Hahn, Duplaga, and Hartley (2000) state that improved customer satisfaction can be achieved through good integration of functional activities. In order to improve efficiency and effectiveness in managing business processes that produce and deliver goods and services, it requires the integration of operations management and information systems both within the organisation and with the supply chain members (Barnes, Hinton & Mieczkowska, 2003). The results of a study by Rosenzweig, Roth and Dean (2003) indicate that supply chain integration intensity improves business performance. In summary, based on the previous studies in the literature, it is shown that integration of operations can improve order fulfilment in an organisation. However, little is known concerning the impact of SCI operational factors on order fulfilment in public hospitals. This leads us to propose the following hypotheses (H3a H3e): H3a: Supply chain integration initiatives have positive influence on order fulfilment. H3b: Organisation strategy and supply chain integration drivers have positive influence on order fulfilment. H3c: Performance improvement and supply chain integration have positive influence on order fulfilment. H3d: Organisation environment forces have positive influence on order fulfilment. H3e: Barriers to supply chain integration have negative influence on order fulfilment. Proposed Model: Based on the literature review on SCI and order fulfilment, we propose a conceptual model and five relevant hypotheses (Figure 1). The construct with combinations OS & SCI, and PI & SCI were caused by exploratory factor analysis. 404

6 SCI operational factors \ Figure 1. Research model and hypotheses RESEARCH METHODOLOGY Survey research approach was used in this study because it was useful to collect information on the type of the problem in this study, examine relationships between variables, and test hypotheses. Data collection is conducted based on the procedures such as information needs, sampling design, instrumentation, data collection, data processing, and report generation (Fowler 2009, Alreck & Settle 2004). Our research considers all New Zealand public hospitals to test the proposed hypotheses. The survey questionnaire was sent to the population. New Zealand has 21 District Health Boards (DHBs) and 40 public hospitals, which provide services to 4.2 million people. Initially, in order to effectively design and validate the survey questionnaire before administration, a comprehensive literature review was conducted to identify scales used in past studies to measure the constructs. Afterwards, we conducted preliminary interviews with senior purchasing and supply executives from a number of hospitals which provided additional scale items related to public hospital operations. SCI operational issues (factors) from Fawcett and Magnan (Fawcett & Magnan 2001) were adopted for the survey questionnaire as they were similar to the responses from the preliminary interviews. Based on the selected variables, a model with five hypotheses was developed. The scales were validated using Churchill s paradigm (1979) to ensure that a valid and reliable scale was developed for the purpose of this study. Before conducting the pilot study, the survey questions were reviewed for content, clarity and ease of understanding by three academics and by two senior purchasing and supply executives from New Zealand public hospitals. 405

7 The sample size for the pilot study was composed of 150 purchasing and supply personnel directly involved in purchasing goods and services for the public hospitals. After several reminder s within a month period, we received 12 usable responses (8% response rate). The sample was too small for rigorous statistical testing, but the responses were enough to determine important measurement items for the main survey. The T- test indicated that there was no significant non-response bias in the data received from the pilot study. Based on the results of the pilot survey, a revised survey questionnaire for the main study was sent to the population of 350 purchasing and supply personnel in all 21 New Zealand DHBs and 40 public hospitals. 8 questionnaires were returned due to change of address or the contact person was no longer at the hospital. A total of 60 usable responses were received representing 17.2%. The Levene s test for equality of variances was used to evaluate the assumption whether the population variances of the two groups (responses and non-responses) were equal. The result showed that the variances were relatively equal, p > Therefore, there was no significant non-response bias in the data received from the main study. DATA ANALYSIS AND HYPOTHESIS TESTING Assessment of the Normality The data were assessed to determine normality of distribution because factor analysis and multiple regression analysis both require variables to be normally distributed. A visual examination of the normal probability plots of the residuals (errors in predicting sample data) indicates a normal distribution of the values and meets the assumption of normality. Normality of the distribution of the variables was checked through outliers. The outliers were checked using the partial regression plots which helped to identify influential observations for each independentdependent observations relationship (Hair, Black & Babin 2006). All the variables were well represented by the relationship and they could not affect the partial correlation. A variable with an absolute value of Kurtosis index greater than 10.0 indicates there is a problem with normality and values greater than 20.0 indicate a more serious normality problem (Kline & Santor 1999). The acceptable absolute value of skewness and kurtosis should not exceed three and ten respectively. The actual deviation from the normality of distribution was determined using skewness and kurtosis. The SPSS software was used to check both skewness and kurtosis and the result (Table 1) showed that the absolute values were within the acceptable levels (i.e., Kurtosis index < 10.0 and Skewness index < 3.0), which means there was univariate normality. In addition, the visual assessment of normal probability plots indicated that there was no serious deviation from normality. Three different approaches such as principal component analysis with varimax rotation, the scree plot, and Cronbach s alpha (i.e., items with high inter-item correlation were selected) were used to determine the final number of measurement items required for multiple regression. In order to assess unidimensionality, we used exploratory factor analysis for each construct (Hair, Black & Babin 2006). The factor loadings for each construct are indicated in Table 2. The measurement items have factor loadings between and exceeding a minimum threshold value of 0.6 acceptable in the literature for new scales (Nunnally & Bernstein 1994). 406

8 Reliability Analysis and Construct Validity The scale reliability feature of SPSS version 17 was used to determine reliabilities for each construct using Cronbach s alpha (measure of reliability). Table 2 also shows the reliabilities of the final constructs. The reliabilities of newly developed constructs met a minimum value of alpha (0.6) recommended in exploratory research, and the adapted constructs had reliabilities between (close to minimum 0.7) and which are acceptable for the scales (Hair, Black & Babin 2006). Exploratory factor analysis provides support for acceptable convergent validity. Table 2 shows high factor loadings on a factor that indicate they converge on some common point. A good rule of thumb is that standardized loadings estimates should be 0.5 or higher indicating that variables in each construct are highly correlated and reliable, and ideally 0.7 or higher (Hair, Black & Babin 2006). The indicators or variables in each construct (Table 1) are highly inter-correlated and highly reliable, showing that all indicators are measuring the same (latent) construct (Lee 2000). The convergent validity of the scales was determined by checking the individual item correlations. Table 1: Measures of the constructs and descriptive statistics Construct/ Mean Std. Deviation Skewness Kurtosis Items Supply chain integration Initiatives (SI) Cross-functional process integration within the hospital (SI1) Integration with customers (SI2) Organisation strategy and SC1 drivers (ST) Our organisation s corporate strategy includes SC1 (ST1) We have a centralised purchasing department (ST2) Performance improvement and SC1 (SP) Ability to handle expected challenges (SP1) Lowering cost of purchased items (SP2) Hospital profitability (SP3) Table 5.1 (cont.) Organisation environmental forces (SE) Suppliers have initiated integration effort (SE1)

9 Customers have initiated integration efforts (SE2) Barriers to SC1 (SB) A lack of willingness to share information (SB1) Difficult to establish relationships based on shared risks and rewards (SB2) Inappropriate information systems (SB4) Order fulfilment (OF) We classify inventories according to their importance (OF1) Construct/ Mean Std. Deviation Skewness Kurtosis Items Order fulfilment (OF) cont. We have collaborative planning, forecasting and replenishment (CPFR) (OF2) We make an effort to control ordering costs (OF3) Note: Calculations are based on 60 measurement items and used 5-point Likert scale. 408

10 Table 2: Factor loading, reliability and evidence of convergent validity (significant at the 0.01 level) Construct Measurement item Loading Cronbach s alpha Pearson correlation Supply chain integration SI initiatives (SI) SI Organisation strategy and ST SCI drivers (ST) ST Performance improvement SP and SCI (SP) SP SP Organisation SE environmental forces (SE) SE Barriers to SCI (SB) SB SB SB Order fulfilment (OF) OF1 OF OF Note: SI1 = Cross-functional process integration SI2 = Integration with customers ST1= Organisation s corporate strategy including SCI ST2= Centralised purchasing department SP1= Ability to handle expected challenges SP2= Lowering cost of purchased items SP3= Profitabillity SE1= Suppliers initiated integration efforts SE2= Customers initiated integration efforts SB1= Lack of willingness to share information SB2= Lack of shared risks and rewards SB4= Inappropriate information systems OF1= Classifying inventories according to their importance OF2= Collaborative planning, forecasting and replenishment OF3= An effort to control ordering costs. The indicators or variables in each construct (Table 2) are highly inter-correlated and highly reliable, showing that all indicators are measuring the same (latent) construct (Hair, Black & Babin 2006). The variable SB3 was removed due to low inter-correlation. Measures of the constructs and descriptive statistics are indicated in Table 1. The convergent validity of the scales was determined by checking the individual item correlations. The measurement item correlations in each construct are between and There is evidence that the scales show strong convergent validity and they are adequate for measurement of the regression model. 409

11 Multiple Regression Analysis and Test of Hypotheses Multiple regression analysis predicts the relationship changes in the dependent variable in response to changes in the several independent variables (Forza 2002). In this research, we used multiple regression analysis to test the relationships between the constructs based on the hypothesised model (see Figure 1). Regression analysis results showed that all five tested hypotheses have positive influence on order fulfilment. Summary results of the hypotheses testing with critical factors are indicated in Table 3. Collinearity diagnostics of the SPSS version 17 were used to test for potential multicollinearity effects. Two measurements of multicollinearity were used in this study: tolerance and condition index. The regression analysis of all the hypotheses indicated tolerance (> 20) and condition indices (< 30) showing that there was no significant multicollinearity effects (Hair, Black & Babin 2006). Supply chain integration and influence on order fulfilment The regression results are indicated in Table 3. Hypothesis Ha: Supply chain integration initiatives have positive influence on order fulfilment. The regression results present moderate support for this hypothesis. The hypothesis is statistically significant at p = 0.01 level for the relationship between supply chain initiatives and collaborative planning, forecasting and replenishment (R² = 0.126, F= 4.127, p = 0.021), with one independent variable, cross-functional process within the hospital having a moderate positive impact on the dependent variable collaborative planning, forecasting and replenishment (β = 0.243, t = 1.447, p = 0.153). Organisation strategy and order fulfilment Hypothesis Hb: Organisation strategy and supply chain drivers have positive influence on order fulfilment. The regression results provide strong support for this hypothesis. The hypothesis is statistically significant at 0.01 level for the relationship between organisation strategy and SCI drivers and order fulfilment (classify inventories according to their importance measure) (R² = 0.147, F= 4.9, p = 0.01), with two independent variables, organisation s corporate strategy includes SCI, having a strong positive impact on the dependent variable classify inventories according to their importance (β = 0.296, t = 2.201, p = 0.032), and another independent variable, centralised purchasing department, having a moderate positive impact on dependent variable (β = 0.150, t = 1.117, p = 0.269). In addition, the hypothesis is statistically significant at 0.01 level for the relationship between organisation strategy and SCI drivers and collaborative planning, forecasting and replenishment (R² = 0.245, F = 9.253, p = 0.000), with independent variable organisation s corporate strategy includes SCI (β = 0.483, t = 3.824, p = 0.000). Performance improvement and order fulfilment Hypothesis Hc: Performance improvement and supply chain integration have positive influence on order fulfilment. 410

12 The regression results provide strong support for this hypothesis. The hypothesis is statistically significant at p = 0.01 level for the relationship between performance improvement and SCI, and order fulfilment (classify inventories according to their importance measure) (R² = 0.115, F = 2.427, p = 0.075), with one independent variable, ability to handle expected challenges, having a positive impact on the dependent variable classify inventories according to their importance (β = 0.382, t = 2.220, p = 0.030). Also, the hypothesis is statistically significant at p = 0.01 level for the relationship between performance improvement and SCI and order fulfilment (an effort to control ordering costs measure) (R² = 0.369, F = , p = 0.000), with one independent variable hospital profitability, having a positive impact on the dependent variable an effort to control ordering costs (β = 0.647, t = 5.213, p = 0.000). Organisation environment forces and order fulfilment Hypothesis Hd: Organisation environment forces have positive influence on order fulfilment. The regression results furnish moderate support for this hypothesis. The hypothesis is statistically significant at p = 0.01 level for the relationship between organisation environmental forces and order fulfilment (collaborative planning, forecasting and replenishment measure) (R² = 0.137, F = 4.515, p = 0.015), with one independent variable, customers have initiated integration efforts, having a positive impact on the dependent variable collaborative planning, forecasting and replenishment (β = 0.343, t = 2.325, p = 0.024). Barriers to supply chain integration and order fulfilment Hypothesis He: Barriers to supply chain integration have negative influence on order fulfilment The regression results provide strong support for this hypothesis. The hypothesis is statistically significant at p = 0.01 level for the relationship between barriers to SCI and order fulfilment (classify inventories according to their importance measure) (R² = 0.359, F = , p = 0.000), with one independent variable, difficult to establish relationships based on shared risks and rewards, having a negative impact on the dependent variable classify inventories according to their importance (β = , t = , p = 0.000). In addition the hypothesis is statistically significant at p = 0.01 level for the relationship between barriers to SCI and order fulfilment (an effort to control ordering costs measure) (R² = 0.299, F = 7.977, p = 0.000), with two independent variables (lack of willingness to share information having a positive impact (β = 0.516, t = 3.182, p = 0.002) and inappropriate information systems having a negative impact (β = , t = , p = 0.002). 411

13 Table 3: The summary results of the hypotheses testing Hypothesis Ha. Supply chain integration initiatives have positive influence on order fulfilment (i. cross-functional process collaborative planning) Hb. Organisation strategy and supply chain integration drivers have positive influence on order fulfilment (i: organisation strategy and SCI drivers; ii: collaborative planning, forecasting, and replenishment.) Hc. Performance improvement and Supply chain integration have positive influence on order fulfilment (i. classify inventory -importance, ii. control order costs) Hd. Organisation environmental forces have positive influence on order fulfilment (i. collaborative planning) He. Barriers to supply chain integration have negative influence on order fulfilment (i. difficulty to establish relationships, ii. lack of willingness to share information and inappropriate information systems) Statistical result R² = 0.126, F = 4.127, p = (i) R² = 0.147, F = 4.9, p = 0.01; (ii) R² = 0.245, F = 9.253, p = (i)r² = 0.115, F = 2.427, p = (ii) R² = 0.369, F = , p = (i) R² = 0.137, F = 4.515, p = (i) R² = 0.359, F = , p = (ii) ) R² = 0.299, F = 7.977, p = Comment (2-tailed) Significant at p = 0.01, Moderately supported (i) Significant at p = 0.01, supported; (ii) Significant at p = 0.05, supported Significant at p = 0.01, supported; Significant at p = 0.05, supported Significant at p = 0.01, Moderately supported Significant at p = 0.01, supported RESULTS AND DISCUSSION This study identified SCI operational factors and their influences on order fulfilment in the public hospitals. We identified the following key influential SCI operational and order fulfilment factors in New Zealand public hospitals: SCI Operational factors Cross-functional process integration Integration with customers Organisation s corporate strategy including SCI Centralised purchasing department Ability to handle expected challenges Lowering cost of purchased items Profitabillity Suppliers initiated integration efforts Customers initiated integration efforts 412

14 Barriers to SCI Lack of willingness to share information Difficult to establish relationships based on shared risks and rewards Inappropriate information systems Order fulfilment factors Collaborative planning, forecasting and replenishment Classifying inventories according to their importance An effort to control ordering costs. Five hypotheses tested (Ha, Hb, Hc, Hd, and He) were found to have positive influence on order fulfilment. The findings suggest that supply chain integration initiatives, especially crossfunctional process within the hospital has a strong positive influence on order fulfilment (i.e., collaborative planning, forecsting and replenishment) (Ha). The more hospitals have a higher level of cross-functional process within each hospital, the more they are likely to have collaborative planning, forecsting and replenishment (i.e., order fulfilment). The finding suports Hahn, Duplaga & Hartley (2000) who argue that improved customer satisfaction can be achieved through good integration of functional activities. The importance of cross-functional process as a requirement of an effective plan for order fulfilment was also identified by other researchers (e.g., Davenport & Prusak, 1998; Smith & Farquhar, 2000). In addition, organisation s strategy that includes suply chain integration has strong positive influence on order fulfilment (i.e., classifying inventories according to their importance and collaborative planning, forecasting and replenishment) (Hb). This finding is in agreement with the work of Min and Yu (2008) who investigated the collaborative planning, forecasting, and replenishment: demand planning in supply chain management. The implementation of colllaborative planning, forecasting and replenishment aimed at improving collaboration between buyer and supplier has been successful in improving order fill rates (Min & Yu, 2008). The hypothesis Hb also was supported regarding the centralised purchasing department having positive influence on order fulfilment (i.e., classifying inventories according to their importance). The results identify that performance improvement and supply chain integration have strong positive influence on order fulfilment (Hc). The ability to handle expected challenges and profitability (Fawcett & Magnan, 2001) have strong significant impact on the order fulfilment (i.e., classify inventories according to their importance) and an effort to control ordering costs, respectively. The results also showed an unexpected finding that performance improvement and supply chain integration do have significant influence on order fulfilment (i.e., collaborative planning, forecasting and replenishment) (Hc). Furthermore, the results demonstrate that organisation environmental forces, such as customers have initiated integration efforts are predictors of order fulfilment (i.e., collaborative planning, forecasting and replenishment), indicating evidence to support Hd. The result confirms the finding of the previous study conducted by Fawcett and Magnan (2001) which revealed customers initiated integration, with higher mean average rating than suppliers initiated integration. As hypothesized, barriers to supply chain integration have negative influence on order fulfilment (He). That is, barriers to supply chain integration factors, such as inappropriate information 413

15 systems and difficult to establish relationships based on shared risks and rewards, have significant negative influence on order fulfilment (i.e., an effort to control ordering costs and classify inventories according to their importance, respectively). This study supports Fawcett and Magnan (2001) and Fawcett, Magnan and McCarter (2008) who identified inadequate informations systems, as the most barrier to effective supply chain integration in an organisation, followed by lack of shared risks and rewards, and lack or willingness to share information. Surprisingly, this study found that lack of willingness to share information has strong positive significant influence on order fulfilment (i.e., an effort to control ordering costs). The results indicate that lack of willingness to share information is a predictor of an effort to control ordering costs. The results of the hypotheses testing discussed above answers the research questions and fulfil the research objective. This study makes a contribution to the process-based management theory by examining the supply chain integration operational factors and their impact on order fulfilment. The study provides a comprehensive understanding of supply chain integration and order fulfilment in public hospitals in New Zealand. CONCLUSION AND FUTURE RESEARCH This study achieved its objective by highlighting the impact of SCI operational factors on order fulfilment in the public hospitals. The research contributes to theoretical and practical knowledge by providing a new model for enhancing SCI and order fulfilment in an organisation. The proposed theoretical model consists of five hypotheses tested using multiple regression analysis. The results support five hypotheses that identify the following critical SCI operational factors which have influence on order fulfilment: integration with customers, establishing centralised purchasing department, lowering cost of purchased items, and inappropriate information systems. The findings on order fulfilment also provide additional implications. The study results shows that order fulfilment can be improved in the hospitals by classifying inventories according to their importance, having collaborative planning, forecasting and replenishment, and make an effort to control ordering costs. Min and Yu (2008) argue that implementation of collaborative planning, forecasting and replenishment has been successful in minimizing safety stocks, improving order fill rates, increasing sales, and reducing customer response time. Therefore, results of this study are consistent with the findings of Min and Yu (2008). Thus, managers have to pay attention to collaborative planning, forecasting and replenishment in order to fulfil orders effectively. Furthermore, this study identified three critical barriers to supply chain integration: lack of willingness to share information, difficult to establish relationships based on shared risks and rewards, and inappropriate information systems. Lack of willingness to share information is the most critical barrier of supply chain integration that managers should consider seriously. This finding does not support Fawcett and Magnan (2001) and Fawcett, Magnan and McCarter (2008) who found inappropriate information systems as the most critical barrier to supply chain integration. Managers should focus more on the information input in the appropriate information system for an organisation. Researchers and practitioners can use the survey instrument developed and tested in this study for understanding the general nature of operational supply chain integration factors and their impact on order fulfilment. 414

16 Like any research this study has limitations. We used in our study a survey instrument developed initially from the interviews with three procurement executives and the literature. Future research may start with more than three interviews. The sample size of the pilot study was only 12 (usable responses), not sufficient for rigorous statistical analysis. The survey instrument was developed based on expert opinion from New Zealand, and the survey was conducted in New Zealand. The organisational features and practices of New Zealand public hospitals may not have exact similarity with other country s hospitals. Despite these limitations, the study provides many future research opportunities. Although the research was conducted in the New Zealand public hospital sector, the results have implications for the private hospital sector in other countries and different types of organisations, which are interested in enhancing supply chain integration. Also, a study comparing the nature of supply chain integration in public and /or other private hospital sectors can add value to the literature. Future research could further explore the impact of sustainable operational supply chain integration factors on customer relationships, demand, and returns (reverse) management. An additional future area for research is to conduct a longitudinal study on supply chain integration as perceived by operational, middle and senior management in public and private hospitals or other organisations by sector. Furthermore, we believe that this research identified a research gap and fullfilled the stated objectives by making a notable contribution to the health care supply chain discipline. REFERENCES Akkermans, HA, Bogerd, P, Yucesan E & Van Wassenhove LNV 2003, The impact of ERP on supply chain management: Exploratory findings from a European Delphi stud, European Journal of Operational Research, vol. 146, no. 2, pp Alreck, PI & Settle, RB 2004, The survey research handbook, McGraw-Hill/Irwin, New York. Armstrong, JS, Brodie, RJ & Parsons, AG 2001, Hypotheses in marketing science: literature review and public audit, Marketing Letters, vol. 12, no. 2, pp Barki H & Pinsonneault A 2005, A model of organizational integration, implementation effort, and performance, Organization Science, pp Barnes, D, Hinton M & Mieczkowska S, 2003, Competitive advantage through e- operations, Total Quality Management & Business Excellence, vol. 14, no. 6, p Bowersox, DJ, Closs, DJ & Stank, TP 2000, Ten mega-trends that will revolutionize supply chain logistics, Journal of Business Logistics, vol. 21, no.2, pp Breen, L & Crawford, H 2005, Improving the pharmaceutical supply chain: Assessing the reality of e-quality through e-commerce application in hospital pharmacy, International Journal of Quality & Reliability Management, vol. 22, no. 6, pp Bhakoo, V & Chan, C 2011, Collaborative implementation of e-business processes within the health-care supply chain: the Monash Pharmacy Project, Supply Chain Management: An International Journal, vol. 16, no. 3, pp Brennan, CD 1998, Integrating the healthcare supply chain. Healthcare financial management, Journal of the Healthcare Financial Management Association, vol. 52, no.1, pp. 31. Byrnes, J 2004, Fixing the healthcare supply chain, Harvard Business School Newsletter, p Campbell, J & Sankaran, J 2005, An inductive framework for enhancing supply chain integration, International Journal of Production Research, vol. 43, no. 16, pp

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