Questionnaire to be filled to cover all areas in the attached dissertation propo

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Questionnaire to be filled to cover all areas in the attached dissertation proposal file named: Order 373157426 Lean Sigma F 3 (3).docx, like Research Problem, Research Gap, and Methodology
also, fill up the word file named QUESTIONNAIRE Letter.docx
. Research Problem
The problem is that overwhelmed hospitals across the world experienced extreme medical supply shortages during the Covid-19 public health crisis, exposing the need for maximized inventory management designs and state-of-the-art technology. Healthcare supply chain optimization, including adequate inventories, during public health crises are critical to population sustainability and vitality (Knot, 2020; Pongtriag & Matkaew, 2022).
A. Research Aims and Objectives
The aim of the proposed study is to measure the effects of LSS and technology upgrades on Sohar Hospital inventory management processes via survey questionnaire administration to Sohar staff and North-Batinah community members and statistical analysis of the survey data. The research objectives are as follows:
O1: Gather perspectives of Sohar Hospital staff and patients regarding the efficiency of Sohar Hospital healthcare delivery.
O2: Quantitatively measure the effects of LSS on Sohar inventory management processes.
O3: Quantitatively measure the effects of technology upgrades on Sohar inventory management processes
B. Research Question
The research will address the following research question:
R1: How can LSS implementation and healthcare technology upgrades aid Sohar Hospital in the mitigation of spikes in hospital capacity and further insulate the hospital inventory management system from global healthcare crises in the future?
 
III. Literature Review
Bhattacharyya, Shapiro, and Schneider (2022) argued that healthcare system innovation toward more intelligent system management models and digital applications is “accelerated” as a Covid-19 response. A large part of the innovation movement is the adoption of LSS. Sohal et al. (2022:216) defined LSS as a “post-modern management control” ideology suitable for enterprise management control strategies. The definition accounts for advancements in technology and public health crises unique to the 21st century. Improta, Borrelli and Triassi (2022:2) argued that “healthcare process optimization” approaches “borrowed” from the manufacturing sector, such as LSS and machine/deep learning algorithms, are central to healthcare efficiency. MENA public health infrastructures benefit from post-modern corporate management tools (Ibrahim et al. 2022). Moreover, the improvements to healthcare system efficiency and effectiveness lead to proposals for new automated technology designs (Improta, Borrelli & Triassi, 2022).
Public health crises can be mitigated by high-level of preparedness and rapid, effective response (Taha, 2021). Neve and Schmidt (2022:126) argued that hospital financial objectives require “accurate and consistent captures” of the hospital’s inventory use. Hundal et al. (2020) conducted a narrative literature review to investigate how much LSS can mitigate Covid-19 effects on the healthcare environment. The three primary topics were “personal safety, telemedicine, and process redesign” (Hundal et al. 2020:1). The researchers also supported that LSS implementation amplifies risk management strategies to minimize process variations; thus, LSS minimizes uncertainty and potential business discontinuity. The philosophy is accurate as multiple enterprises have reported positive LSS implementation results (Sohal et al. 2022; Mahmoud et al. 2021; Improta, Borrelli & Triassi, 2022). Sohal et al. (2022) investigated critical success factors (CSFs) of LSS implementation in healthcare environments. Approximately 62 LSS projects were analyzed based upon a grounded theory methodology. The researchers identified positive relationships between the CSFs and the achievement of continuous improvement objectives.
Taha (2021) argued that the Gulf states’ reliance on foreign medical supplies, equipment, and medical professionals is excessive and must be addressed by transport and travel controls. Al-Jabri et al. (2021) extracted healthcare staff and patient perspectives regarding healthcare quality in Oman. Participants completed a total of 507 survey questionnaires regarding patient safety and quality of care. The responses reflected high ratings for quality of care, hospital staff competency, and patient satisfaction. Further, O’Mahoney et al. (2021) implemented LSS to maximize supply chain bottom lines in a private hospital.
A. Research Gap
Although the literature regarding healthcare sector supply chains and operations is increasing (Ali & Kannan, 2022), proposals for more effective inventory models for hospitals supported by ministries of health in Gulf Cooperation Council (GCC) countries are lacking. Much of the current work is a type of systematic review published prior to the SARS-CoV-2 outbreak. Therefore, further research regarding inventory management strategies and state-of-the-art technologies for healthcare facilities in the GCC states is needful.
 
IV. Methodology
The method is a quantitative analysis using a survey questionnaire administered to Sohar Hospital staff, patients, and local community members. Survey questionnaires are of the most common approaches to the development of enterprise process improvement strategies (O’Connor, 2021). Recall that Al-Jabri et al. (2021) conducted a similar study regarding healthcare quality in Oman by extracting the perspectives of healthcare staff and patients. Further, Karani and Osoro (2020) administered a survey to 200 Tran Nzoia hospital employees to investigate inventory management and medical service delivery.
A. Research Philosophy
Constructivist philosophy underpins the quantitative survey research design for this study due to the systems theory and technical aspects of the topic, along with the systematic nature of the data collection and analysis approach. Agoplan (2022) defined constructivism as “a learning theory” of knowledge acquisition and successfully applied tenets of social constructivism to a Covid-19 era online schooling environment. Prior to 21st-century ‘smart’ technology and electric cars, Forster (1999) used the constructivist theory as a basis for a technology-based research design. Magos (2021:1) argued that survey research cannot build upon “positivist epistemological assumptions”, particularly concerning the social sciences. Moreover, Boon, Orozco and Sivakumar (2021) argued that complex post-modern problems require capable research, which is not fully possible using empiricist designs.
B. Research Design
For the proposed study, a close-ended survey will be administered electronically via the Survey Monkey or Facebook Survey platform. A deductive research design was selected based on the need to collect and analyze data to answer the research question. Mohajan (2020) described quantitative research as a deductive, and systematic approach to problem-solving. Moreover, Bihu (2021) described survey questionnaires as practical and economical vehicles for data collection.
The criteria for participation in the survey are 1) Sohar, Rustaq, or Nizwa resident; 2) 18 years of age or older; 3) Sohar Hospital staff member, patient, visitor, or relative of a Sohar Hospital staff member or patient. Potential survey participants will be solicited by email and social media. A primary concern of such survey research designs is response rates, as survey response rates have decreased significantly in the past 20 years (Doss et al. 2020). In addition, the number of surveys administered to the “general public” has caused “survey fatigue” in many cases (Doss et al. 2021:311). However, Mohajan (2020) supported that quantitative research designs with statistical analysis realize accurate outcomes. Further, Bihu (2021:1) argued that, due to the practicality of the process, survey methods now “dominate” research design options, especially for researchers in developing economies.
C. Sample Population Demographics and Data Collection
The sample population for the survey will include Sohar Hospital administration and staff and Sohar patients. Data will be collected from approximately 50 to 100 participants electronically via email. Participants will sign a consent form prior to accessing the survey. The survey will solicit current perspectives, attitudes, and experiences of the Sohar Hospital staff and patients and the local population (Vatovec & Hanley, 2022).
D. Data Analysis
The survey design is a total of 12 close-ended questions with an option of four to five multiple-choice answers. The collected data coded design is according to a 5-point Likert scale. Survey data analysis will consist of descriiptive statistics and multiple regression. Along with averages and standard deviations, multiple regression will be used to measure the following metrics as variables (Saad et al. 2020; Indeed, 2022; Neve & Schmidt, 2022):
• Inventory Value Optimization – Supply chain fulfilment efficiency
• Service process cycle time – Common hospital services delivery times
• Process capability – Which inventory controls affect service delivery the most
• Patient satisfaction – How Sohar patients rate the hospital services
• Process ranking – Which inventory processes are most critical
• Industry benchmark – How Sohar compares to other Omani public hospitals
The regression model will quantify correlations between inventory management metrics and healthcare service quality (Chaudhary et al. 2022).

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