Healthcare industry is directly linked with human lives and face plaguing problems. Therefore, healthcare facilities minimize risks associated with deficiency of medicines or equipment. This study was carried out to find the dimensions of disruptive factors affecting inventory control at public healthcare facilities. From different healthcare facilities of District Sahiwal and Pakpattan 100 respondents were selected by utilizing random sampling. Then, Exploratory Factor Analysis was done in accordance to congregate the study objectives with a structured questionnaire. The results of this study determined two dimensions for each construct. Lastly, a test of reliability was conducted to find the acceptance level. This study broadens the scope of inventory control to healthcare. However, the study was geographically limited and thus, should be extended to other regions as well. Further, for sustainable performance, the study results should act as an enlightening figure for government and especially the healthcare facilitators in the identification of problems.
Keywords: EFA, Factor analysis, Information technology, Staff skills,Procedures,Inventory accuracy, Stock out, Inventory management, Healthcare management, Public healthcare.
JEL Classification: C38, C88, G31, I18, D83, K49.
Received: 4 August 2020 / Revised: 8 September 2020 / Accepted: 21 September 2020/ Published: 5 October 2020
This study is one of very few investigating the dimensions of disruptive factors and inventory control. The study contributes, identifying the dimensions within the constructs, to the existing literature as well as the reliability of those constructs and their relevant dimensions.
Inventory control system effectively stimulates and directly affects the organizational performance. When “inventory” comes to healthcare sector, it is purchased but not hitherto dispensed medicines. Therefore, hospitals purchase and hold priciest therapeutic inventory items to congregate potential future transactions by ensuring its availability (Hashmi, Amirah, & Yusof, 2020b). Whereas, stocked-out affects healthcare services (Maini et al., 2014). Healthcare providers imperatively persuade stochastic demand to avoid human mortality (McPake et al., 2013). A research in Ghana indicated 50% of all deaths happen due to non-availability of essential medicines. In budget 2015-16, Punjab Provincial Assembly provided a hefty amount of “168 billion” Pakistani Rupees (PKR) to Department of Health for primary and secondary healthcare. Despite of having 168 billion PKR, the Health Department found expired batches of curative drugs and stock-out of medical accessories at Punjab Institute of Cardiology (PIC), Lahore. This resulted deaths of 131 heart patients and compelled the Health Department to procure medicines and accessories of worth 5.6 billion PKR only for PIC, which was a huge amount (Rashid & Amirah, 2017). It is therefore concluded that the deficiencies in stock of medicines and accessories are posing major concerns.
1.1. Research Questions and Objectives
To curtail the stated issues, the study needed to lay a considerable emphasis by finding the functions of healthcare facilities, their responsibilities, and mechanism through effective inventory control processes. Therefore, this study emphasized on following objectives:
2.1. Bureaucratic Procedures and Inventory Control
Bureaucracy is one of the most dominant counterproductive stimuli in rigid business policies. The bureaucrats enforce the employees to act for unconditional conformity on procedures, rules and policies without caring the displacement of organizational goals (Dietl, 2015). Furthermore, Udy (1959) stated that people often remain busy to address rigid rules and lose attentions from real purpose of the firm; resulting displacement of effectiveness. Moreover, inventory dysfunction or unanticipated consequences might occur due to rigid rules and policies, which ignites reluctance against environment change, limits the appliance of knowledge, and limits the collective efforts of teams (Blau, 1955; Yaver, 2016). In addition, Blau (1955) expressed that rigid structured policies and rules encourage the managers with bureaucratic personality and could be fatal. Udy (1959) added; as negative consequences of structural bureaucracy. The agile solutions are rarely anticipated by rigid organizations. For this reason, organizations suffer expensive inventories, lengthy lines, useless procedures, bribes and unfriendly bureaucrats. Moreover, it originates maladaptive, intensified intolerance, overreliance on control and provocation of uncertain situations (Moskovich, 2014). Generically, public sector organizations often facade red tape nuisances (Tummers, Weske, Bouwman, & Grimmelikhuijsen, 2016) and reducing the checks can avoid red tapes with increased effectiveness (Kaufman, 2015).
2.2. Information Technology and Inventory Control
Today is the world of Information Technology (IT). IT includes information systems, which integrate different functional units of an organization (Davenport, Quigley, Martin, Holt, & Arthington, 2000). Technologies infuse new business procedures (Christensen, 2013) and technology enforces the companies to adopt automation (Lee & Whang, 2000). Whereas, in supply chain; stock-outs are becoming pivotal problem as recognized by practitioners and researchers (Hashmi et al., 2020b; Vasconcellos & Sampaio, 2009). Stock-outs change the shopping attitude and buying behavior (Rani & Velayudhan, 2008). Therefore, technology offers new techniques of handling stock-out situations (Avlijas, Simicevic, Avlijas, & Prodanovic, 2015). In addition, being non-technological in modern businesses is a decisive challenge due to which stocked-out and inventory inaccuracies are originating huge losses (Rashid., 2016). A study found 70% inaccurate inventories in stock keeping units (Raman, 2000). Meanwhile, use of technology increase the accuracy, deliver in-time information, and fast data entry (Cakici, 2012). Hence, to gain competitive edge it is important for a firm to adopt IT and before adaptation, diffusion of knowledge is necessary to conclude their needs (Dostie, 2013).
2.3. Staff Skills and Inventory Control
For employee’s growth to develop good sense of humor, the staff training has drastically grown since 1970s (Rehman, Khan, & Khan, 2011). Therefore, Complex quantities and ordering time presents challenges to inventory administration and imperatively need involvement of designated staff with adequate skills for supply chain management. Unfortunately, inventory control found skill gaps, especially in hospital pharmacies (Dias, 2011). According to American Society of Health-System Pharmacists (1995) generically, government governing hospitals require pharmacy technicians and pharmacists for drug inventories who are specifically not skilled in inventory control. Therefore, imparting knowledge for skill enhancement is important for diffusion of technology and organizational development (Dostie, 2013). Moreover, it is worthwhile challenging to educate the amateurish (Hummel, Freeland, Craft, & McKellips, 2012). Due to this reason, an increased number of organizations are formalizing and adopting the skill enhancement programs. In addition, Van der Klink and Streumer (2002) found significant improvement in staff skills between before and after On the Job Training (OJT). However, persistence of inappropriate training especially in automated inventory control applications are entrenching inventory control negatively (Hashmi, Amirah, & Yusof, 2020a). Therefore, it is certain that untrained workers are often solicited to execute tasks about which they are ignorant. In response they deny or end up (Johnson, 2015). However, relevant skills and qualification critically required (Dragoni, Oh, Vankatwyk, & Tesluk, 2011).
This research used quantitative research design and carried-out EFA procedure for scales’ validation of items through Statistical Package for Social Sciences (Amirah, Asma, Muda, Amin, & Him, 2019). Furthermore, Factor Analysis was examined to find the relationship between items’ shared common variances and the individual item variances. Moreover, the communalities were measured to find the ratio of item’s unique variance to its shared variance. Later, the study used Varimax rotation with Principle Axis Factoring (PAF) to measure the structure for the items. In Varimax rotation, the factors remain independent and the resultant factors considered as much uncorrelated as possible to each other. Lastly, factor rotation was used to interpret the underlying structures of the factors.
3.1. Data Collection
Primary data was collected through structured questionnaires from managerial staff managing inventories at healthcare facilities located at districts of Sahiwal and Pakpattan (Pakistan). Whereas, secondary data was collected from healthcare professionals, inventory management professionals, websites, business management journals, handbooks, published reports, different medical journals, and document reviews.
3.2. Target Population, Sampling Technique, and Sample Size
Selected target population was 147 healthcare facilities located at districts of Sahiwal and Pakpattan (Pakistan). To generalize the observed characteristics, a simple random sampling was used and 100 respondents were chosen for data collection (Rashid, Amirah, & Yusof, 2019).
Kaiser-Meyer-Olkin (KMO) was used to measure sample size adequacy. The KMO results in Table 1 expressed that the KMO values for all constructs (bureaucratic procedures, information technology, staff skills, and inventory control) are > 0.6 which shows, the size of sample is adequate and is fit for factor analysis (Beavers, Lounsbury, Richards, & Huck, 2013). Additionally, the Bartlett test of Sphericity is < 0.000, which is significant for each variable and is acceptable by providing realistic bases for factor analysis (Beavers et al., 2013; Hashmi et al., 2020a).
For extraction, Principal Axis Factoring (PAF) was applied to measure the divided variance among possible factors. The common criterion for factor extraction is Eigenvalue > 1.0 (Hashmi et al., 2020a). Therefore, first two factors were extracted for each construct and have been shown in Table 2; i.e., bureaucratic procedures, information technology, staff skills, and inventory control. Eigenvalue less than 1.0 tend to cause the factors with over extraction and explain less information to keep that factor (Hashmi & Tawfiq, 2020). In addition, a total of > 60 percent of the change in total variance was contributed by extracted factors for each variable (Awang, 2015).
Table-1. KMO and Bartlett’s test.
Bureaucratic Procedures |
IT |
Staff Skills |
Inventory Control |
||
| Kaiser-Meyer-Olkin Measure of Sampling Adequacy. | .855 |
.870 |
.828 |
.852 |
|
| Bartlett's Test of Sphericity (Sig.) | Approx. Chi-Square | 490.264 |
467.484 |
472.759 |
360.645 |
| Df | 36 |
36 |
28 |
28 |
|
| Sig. | .000 |
.000 |
.000 |
.000 |
|
Table-2. Total variance explained.
Factor |
Initial Eigenvalues |
Rotation Sums of Squared Loadings |
||||
Total |
% of Variance |
Cumulative % |
Total |
% of Variance |
Cumulative % |
|
Bureaucratic Procedures |
||||||
1 |
4.481 |
49.790 |
49.790 |
3.162 |
35.129 |
35.129 |
2 |
1.869 |
20.772 |
70.563 |
2.477 |
27.527 |
62.656 |
Information Technology |
||||||
1 |
4.293 |
47.696 |
47.696 |
2.984 |
33.152 |
33.152 |
2 |
2.092 |
23.239 |
70.935 |
2.685 |
29.832 |
62.984 |
Staff Skills |
||||||
1 |
4.263 |
53.282 |
53.282 |
2.824 |
35.303 |
35.303 |
2 |
1.667 |
20.842 |
74.123 |
2.475 |
30.940 |
66.243 |
Inventory Control |
||||||
1 |
3.899 |
48.731 |
48.731 |
2.567 |
32.087 |
32.087 |
2 |
1.710 |
21.371 |
70.102 |
2.264 |
28.295 |
60.382 |
Table 3 expressing the communalities score and factor loadings against each item foe their respective construct. The communalities scores are greater than the cut-off value (0.2) for each item, which mean that it will not signify the additional factors (Child, 2006). Additionally, the communality loadings between 40 and 60 are taken as low to moderate (Costello & Osborne, 2005) between 50 and 60 as acceptable (MacCallum, Widaman, Zhang, & Hong, 1999) and > .70 is ideal (Beavers et al., 2013). Lastly, the Rotated Factor Matrix columns of Table 3 contained the factor loadings for each item under their respective variables. Based on Rotated Factor Matrix, the factor loadings for all items were separated into Factor 1 and Factor 2 for each construct from the one with highest loading/weight to the lowest loading.
The “bureaucratic procedures” and “information technology” both are consisting same results by having nine items for each variable (item1 to item9) and separated into two factors; namely, Factor 1 and Factor 2 in 3 iterations. Factor 1 constituted items 1, 2, 3, 4, and 5; while Factor 2 constituted items 6, 7, 8, and 9. Whereas, “staff skills” and “inventory control” comprising eight items for each variable (item1 to item8) with two factors in 3 iterations; namely, Factor 1 and Factor 2; where Factor 1 comprised items 1, 2, 3, and 4; while Factor 2 have items 5, 6, 7, and 8. Finally, the factor loadings are > 0.512 and consider as significantly stable (Hair, Black, Babin, Anderson, & Tatham, 2006; Pituch & Stevens, 2015).
Table-3. Communalities and rotated factor matrix.
| Bureaucratic Procedures | Factor |
|||
| Items | Statement | Comm* |
1 |
2 |
| B1 | In our organization, there are adequate standing operating procedures on inventory issues? | .807 |
.898 |
|
| B2 | Have you experienced long bureaucratic related purchase difficulties? | .691 |
.807 |
|
| B3 | Do the Storekeepers have full independence in performing their daily duties? | .430 |
.800 |
|
| B4 | To what extent, do you agree that long bureaucratic practice affects inventory control/management? | .716 |
.708 |
|
| B5 | In our organization, we have over reliance on and do adhere to inventory policies? | .566 |
.620 |
|
| B6 | Do the Storekeepers have a power to advice the management about stock matters? | .547 |
.810 |
|
| B7 | Our organization management is involved in inventory planning with minimum red tapes. | .658 |
.746 |
|
| B8 | During Stock review, we face too much red tapes and paper work in providing feedback about good or poor performance by comparing the actual situation to the government established and documented standards and regulations. | .579 |
.737 |
|
| B9 | The entire function needs thorough improvement with least paper work. | .647 |
.704 |
|
| Information Technology | ||||
| IT1 | Information management system is better than manual systems. | .691 |
.812 |
|
| IT2 | The use of information management system is easily understood. | .658 |
.811 |
|
| IT3 | Information management system is more reliable. | .640 |
.782 |
|
| IT4 | In our organization, we use computerized system in managing inventories (such as EDI, EPOS & ERP)? | .570 |
.719 |
|
| IT5 | The use of information management system helps to achieve proper inventory control. | .430 |
.628 |
|
| IT6 | Due to integrated systems, order fulfillment generation reduces the uncertainties. | .697 |
.823 |
|
| IT7 | Due to collaboration with stakeholders, we are able to forecast accurately. | .679 |
.822 |
|
| IT8 | Our organization has close integrated communication with stakeholders. | .636 |
.778 |
|
| IT9 | The made promises are reliable due to automated systems. | .667 |
.760 |
|
| Staff Skills | ||||
| SS1 | Do the Storekeepers have the required competence in performing their duties? | .960 |
.968 |
|
| SS2 | With professionalism in stock control, Storekeepers can help the client to diagnose problems and come up with practical/workable solution. | .676 |
.812 |
|
| SS3 | Inventory control plans are being affected by the involvement of incompetent staff. | .642 |
.738 |
|
| SS4 | Storekeeper or (stock controller) has achieved their purposes for which they were established. | .621 |
.725 |
|
| SS5 | Do you think professional pre /post employment training on inventory control/Supply Chain Management is purposeful at Ministry? | .685 |
.816 |
|
| SS6 | To what extent, do you agree that staff skills in inventory management affect inventory control? | .674 |
.793 |
|
| SS7 | In future, the healthcare facility is planning to pay more attention on; how to use existing opportunities to upgrade skills and knowledge to perform better and have more benefits from it. | .591 |
.727 |
|
| SS8 | Staff and managers focus on educating workers about inventory control and enhancing workers’ attitude towards their jobs to an extent where improvement becomes a natural process. | .451 |
.646 |
|
| Inventory Control | ||||
| Inv1 | We often face stocked-out of crucial items. | .742 |
.825 |
|
| Inv2 | To cater uncertainties we always have buffer stock of inventory. | .656 |
.808 |
|
| Inv3 | Determining inventory order size is crucial at our part. | .661 |
.791 |
|
| Inv4 | In our organization, most of the needed inventories are not being delivered on time. | .493 |
.655 |
|
| Inv5 | Have you experienced discrepancies stock balances? | .606 |
.778 |
|
| Inv6 | Inventory inaccuracy could be improved by exploring new opportunities. | .592 |
.727 |
|
| Inv7 | Physical inventory varies from the system stock. | .532 |
.713 |
|
| Inv8 | In our organization inventory, accuracy is preferably being handled. | .551 |
.678 |
|
Notes: Comm, Communalities.
On the bases of EFA, the factors were renamed with appropriate names. For construct “Bureaucratic Procedures”, Factor 1 and Factor 2 were renamed as “Rigid Rules” and “Red Tapes,” respectively. However, the two factors of “Information Technology” were renamed as “Information Management Systems” and “Collaboration”. Meanwhile, “Professional Qualification” and “Staff Training” were renamed in place of Factor 1 and Factor 2 of construct “Staff Skills”. Lastly, the factors of construct “Inventory Control” were renamed as “Inventory Stocks” and “Inventory Accuracy”.
4.1. Reliability test
Table 4 expressed the summarized results of Cronbach’s Alpha for each construct and their respective dimension. The Cronbach’s Alpha value for the “Bureaucratic Procedures” is (0.87); for “Information Technology” and “Staff Skills” expressing (>.86) and (>0.87) respectively; meanwhile, “Inventory Control” indicating (>0.84). The values are demonstrating realistic internal higher degree of reliability. According to Cronbach (1951) Cronbach’s Alpha values greater than 0.70 express consistent, reliable, and acceptable results.
| Variables | N of Items |
Cronbach's Alpha (N=100) |
| Bureaucratic Procedures | 9 |
.871 |
| Factor 1: Rigid Rules | 5 |
.889 |
| Factor 2: Red Tapes | 4 |
.852 |
| Information Technology | 9 |
.862 |
| Factor 1: Management Information Systems | 5 |
.875 |
| Factor 2: Collaboration | 4 |
.884 |
| Staff Skills | 8 |
.871 |
| Factor 1: Professional Qualification | 4 |
.869 |
| Factor 2: Staff Training | 4 |
.822 |
| Inventory Control | 8 |
.841 |
| Factor 1: Inventory Stocks | 4 |
.853 |
| Factor 2: Inventory Accuracy | 4 |
.899 |
The study empirically measured the variables and found within the prescribed cut-off limits. While analyzing the constructs in EFA, the study found two factors for each variable and all the used items were retained due to fulfillment of criterions. Thus, the factors suggested by Rotated Factor Matrix were renamed appropriately. Lastly, analysis of reliability was conducted which ascertained higher degree of realistic internal reliability and consistency by expressing Cronbach’s Alpha values greater than 0.70 for all construct and the dimensions. The study recommends; the Ministry should integrate their functions for enhanced collaboration with inventory management. Furthermore, there is a need to avoid red tapes by standardizing the procedures; and necessarily educating their staff by special emphasizes On the Job Training programs. Finally, the study will be advantageous for Provincial Ministries, Federal Government, Supply Chain Professionals, Private healthcare facilities, and pharmaceutical industry.
Funding: This study received no specific financial support. |
Competing Interests: The authors declare that they have no competing interests. |
Acknowledgement: All authors contributed equally to the conception and design of the study. |
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