Smart retailing refers to consumer interactions and novel technology targeted at improving shopping experiences, and it is transforming how customers access products, services, and information (Flavián et al., 2020; Pantano and Priporas, 2016; Pantano and Timmermans, 2014). Such purchasing experiences can generate significant social advantages, improve customers' well-being, and occasionally lessen the positive impacts of social inclusion (Dennis et al., 2015).Historically, shopping allowed customers to interact socially with others, which aided in integration and the formation of a feeling of community. With the introduction of electronic channels, customers discovered that they were in close proximity from one another while purchasing online. Given the importance of shopping in our everyday lives, it stands to reason that the retail channel one chooses can influence how people interact, engage, and integrate in their communities. As a result, knowing these options and their consequences can have serious consequences.

Corporate strategy in manufacturing has been a significant topic since the early 1970. This field's specialist’s battle that an association's essential cycles should consolidate tasks the board as a wellspring of long haul upper hand. However, in order to plan, organize, staff, lead, and exercise control throughout the managerial process, all managers must be able to make operational strategic decisions. These options include assistance and product planning, quality management, limit plan, area, style plan, and HR and employment layout, network of stores the board, stock management, booking, and maintenance (Demir, A. 2019). Essential judgments imply the use of physical and visible resources that are intended to provide optimal comfort in aiding mobility or creation (Fan et al., 2017). This sort of choice depends on chiefs' ability for asset arranging, which might help supervisors in adjusting to the necessities of different functional exercises. Long haul office and administration decisions are regularly associated with these exercises.

The infrastructure is the other area of decision. The majority of infrastructure decisions are made using intangible tools like quality, human resources management. However, in contrast to structural elements, infrastructural elements typically do not necessitate the same level of investment. Likewise, paying little mind to less intrigue in infrastructural decisions as per a few examinations, this element is believed to be vital in the help business.

Shopping malls have had a significant impact on and improved the lives of many communities since the early twentieth century (Chotipanich, S. &Issarasak, S. 2017). Customers increasingly prefer these shopping malls as locations to shop, calm down, entertain, and communicate. As people shop, socialize, and create leisure activities simultaneously, these locations have evolved into an entity for the majority of modern societies. The way these shopping centers are run and overseen is a big problem that can make customers and other clients feel more at ease during their visits and encourage them to return.

The purpose of this research is to look into several retail malls in Iran's Tehran region. Ten shopping complexes have been considered because thousands of customers have visited them. They are also among the more popular shopping centers in the area. Its goal is to examine and appreciate the effect of mall operational decision-making regions on consumer well-being.

Study Objective

This study aims to find out how structural and infrastructure decisions affect the well-being of mall customers. The review means to examine different shopping centers in the Tehran region of Iran for this reason. Because they are the most well-known in the area and have attracted thousands of customers, the research will concentrate on ten shopping malls.

Literature Review

Operation management strategy

The global production of services is expanding rapidly and necessitating operations management expertise. As a result, studies in operations management are particularly suited to the service production industry (Halkjær, S., & Lueg, R. 2017). In the service industry, departments of operations management are very important. Even though manufacturing operations and service operations management are somewhat comparable, there is a significant difference. This involves the customers, who have the ability to increase or decrease their mall visits. According to Mohar, Abdullah, & Hoo, the strategic cause of mall service delivery process variation needs to be considered (Mohar et al., 2016). Operations management, marketing, and finance are the three most important departments in any mall management organization (Nemtajela, N., &Mbohwa, C. 2017). Operations management is one of the most important departments because it is in charge of processing each step in the process of turning an input of goods into an output of services.

The planning, programming, and control of those processes are the responsibility of ten strategic decision fields that must be managed by the operations management department. Item and administration plans, area, format, quality administration, limit configuration, work and HR configuration, production network the executives, stock administration, planning, and upkeep configuration are all choice fields. These choice regions or decision fields can be reviewed in two stages: significant choices and infrastructure action decisions (Fan et al., 2017).

Shoppers wellbeing

Satisfaction with a variety of subdomains of the customer's life is one way to define shoppers' wellbeing. That well-being may be promoted in commercial settings like shopping malls (Anderson et al., 2018). According to Rook, "social psychological literature provides compelling evidence that social network involvement is positively linked to health and wellbeing across an individual's life span." This assertion lends credence to that idea. It is understandable that shopping malls improve visitors' well-being because they are social gathering spots. Moreover, Rosenbaum, "shopping malls may enhance customers' wellbeing by incorporating natural green spaces and places for social interactions and relaxation" (Rosenbaum et al., 2016). This attestation further proposes that there ought to be express features of malls that impact clients' success.

Infrastructure Decision Points

Considering the structural decision regions, shopping mall infrastructure selections must be evaluated. This is due to the latter having an operational impact on current costs, with short-term implications for the success of the business. Infrastructure does not always require the same level of investments as structural elements (Okoshi et al., 2019). Furthermore, despite the lack of interest in infrastructure decisions (Sardana, D et al., 2016; Wiengarten et al., 2022), the element is seen to be very important in the service sector. Other parts of infrastructure decision-making may include quality management (Brown, S et al., 2018) and human resource management (Roser, C. 2016; Hill, A. 2020).

Methodology

This study looks into how mall shoppers' well-being is affected by structural and infrastructure decision areas. In this specific circumstance, 1350 clients of a shopping center were given an overview and a poll that covered five of the ten functional key choice regions. Understudies in a tasks the board class acquired the information. They have past venture insight from earlier years. They collected data from seven distinct shopping malls after dividing the students into subgroups. Customers of the shopping mall have been chosen at random. Students have received individual responses to their questions from the visitors. The majority of those tourists were locals. Because the malls were at their busiest from afternoon to night, the survey was carried out during those times. Following conversations with professionals and analysts in this field, review surveys were created. In addition, because of these conversations, it was assumed that the executives, stock administration, booking, and support important decision areas of the store network probably won't be easily seen by customers. As a result, only help and item plan, quality management, limit plan, area, format plan, and HR and job plan factors were taken into consideration. There were two sections to these five regions with choices: essential decisions besides, infrastructural decisions. The overview's information was investigated utilizing IBM SPSS 23, which was utilized for exploratory variable examination and various levelled relapse examination. After that, a hierarchical regression analysis is used to explain how each variable affects customers' levels of shopping happiness. Figure 1 depicts the conceptual paradigm for this investigation. Two operations management specialists and four shopping mall directors in Iran's Tehran Region were contacted via questionnaire. This was done to ensure that the queries were pertinent. Each question on the survey was answered by everyone who responded. The response was given on a Likert scale, with 1 meaning "strongly disagree" and 5 representing "strongly agree."At last, the discoveries were put to use in planning some essential direction and ideas for financial backers in shopping center organizations.

Figure 1: Conceptual model

Results and Discussion

The data was collected in the Iranian city of Tehran. We recruited 1350 people with the goal of balancing the sample in terms of gender, age, and education. Figure 2 depicts the distribution through gender, in which 53% are women and 47% are male.

Figure 2: Gender distribution

The majority of participants were between the ages of 20 and 39. Figure 3 portrays a bunch of the example populace that was youthful between the ages of 20 and 59 and that addressed roughly 64% of the example populace all in all.

Figure 3: Age distribution

The participants' educational attainment is depicted in Figure 4, 45% had a bachelor's degree, 12% had more than a master's degree, and approximately 10% had less than a high school diploma.

Figure 4: Education distribution

Following on from the preceding recommendation, an exploratory factor analysis was suggested to decrease variables that could indicate the number of latent components. According to the current study's findings, there were 7 groups with Eigen values greater than one. Furthermore, those variables explained 68% of the variance. Table 1 display the remaining factor loads, Cronbach's Alpha values, and question category titles.

Table 1: The results of the exploratory factor analysis

To be declared convergent, the average variance extracted (AVE) must be greater than 0.50 and the composite reliability (C.R.) must be higher than 0.70. The findings of discriminant and convergent validation are shown in Table 2.

Table 2: Convergent and Discriminant Validity

In the analysis, the explained variation is represented by the modified R square. It relates to the causes why customers acted the way they did. Table 3 explains this even more clearly.

Table 3: The outcomes of the hierarchical regression analysis

This outcome shows that shopping centres’ underlying choice regions are more critical than their infrastructural vital choice regions. Because of the high expense or complexity of amending regions once they have been initiated, administrators must exercise discretion when selecting structural decision areas.

Conclusion

The study's findings indicated how operational strategic decision areas at shopping malls affect shoppers' well-being. As a result of the findings, it is agreed that the subject of investigation, the chores the board field, remains a miscalculated figure determining consumers' happiness in the Some Region of Iran. This component has the ability to explain around 47% of the explanations for why customers have an unfavourable perception of certain shopping malls, so future study should take it into account. The present research, like many others, is restricted to a specific location: the Tehran region of Iran.The observations and outcomes in this regard cannot be generalized to the whole nation of Iraq. In addition, only six factors were analyzed in this study as infrastructure and structural decision-making areas. Inventory control, maintenance, supply chain management, and scheduling may be investigated as components in future studies to determine their impact on shopper satisfaction.

References

• Flavián, C., Gurrea, R., &Orús, C. (2020). Combining channels to make smart purchases: The role of webrooming and showrooming. Journal of Retailing and Consumer Services, 52, 101923.
• Pantano, E., &Priporas, C. V. (2016). The effect of mobile retailing on consumers' purchasing experiences: A dynamic perspective. Computers in human behavior, 61, 548-555.
• Pantano, E., & Timmermans, H. (2014). What is smart for retailing?. Procedia Environmental Sciences, 22, 101-107.
• Dennis, C., Alamanos, E., Papagiannidis, S., & Bourlakis, M. (2016). Does social exclusion influence multiple channel use? The interconnections with community, happiness, and well-being. Journal of Business Research, 69(3), 1061-1070.
• Demir, A. (2019). THE IMPACT OF STRATEGIC OPERATIONS MANAGEMENT DECISIONS ON SHOPPERS'WELLBEING. Asian Academy of Management Journal, 24(1).
• Fan, Y., French, M. L., Duray, R., & Stading, G. L. (2017). Service strategy to improve operational capabilities in the public sector. The Service Industries Journal, 37(11-12), 703-725.
• Chotipanich, S., &Issarasak, S. (2017). A study of facility management operation strategy in shopping malls: Insights from 4 top-class shopping malls in Bangkok. Property Management, 35(3), 236-253.
• Halkjær, S., & Lueg, R. (2017). The effect of specialization on operational performance: a mixed-methods natural experiment in Danish healthcare services. International Journal of Operations & Production Management, 37(7), 822-839.
• Mohar, A. H. A., Abdullah, F., & Ho, V. B. (2016). Development and validations of a holistic service operations management instrument. Procedia-Social and Behavioral Sciences, 224, 429-436.
• Nemtajela, N., &Mbohwa, C. (2017). Relationship between inventory management and uncertain demand for fast moving consumer goods organisations. Procedia Manufacturing, 8, 699-706.
• Anderson, S., Nasr, L., & Rayburn, S. W. (2018). Transformative service research and service design: synergistic effects in healthcare. The Service Industries Journal, 38(1-2), 99-113.
• Rosenbaum, M. S., Otalora, M. L., & Ramírez, G. C. (2016). The restorative potential of shopping malls. Journal of Retailing and Consumer Services, 31, 157-165.
• Okoshi, C. Y., de Lima, E. P., & Da Costa, S. E. G. (2019). Performance cause and effect studies: analyzing high performance manufacturing companies. International Journal of Production Economics, 210, 27-41.
• Sardana, D., Terziovski, M., & Gupta, N. (2016). The impact of strategic alignment and responsiveness to market on manufacturing firm's performance. International Journal of Production Economics, 177, 131-138.
• Wiengarten, F., Durach, C. F., Franke, H., Netland, T. H., & Schmidt, F. K. (2022). Impact pathways: towards an adapted understanding of the development of operational capabilities. International Journal of Operations & Production Management, 43(13), 50-67.
• Brown, S., Bessant, J., & Jia, F. (2018). Strategic operations management. Routledge.
• Roser, C. (2016). Faster, better, cheaper in the history of manufacturing: from the stone age to lean manufacturing and beyond. CRC Press.
• Hill, A. (2020). Manufacturing Operations Strategy: Texts and Cases. Bloomsbury Publishing