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ISSN : 1598-7248 (Print)
ISSN : 2234-6473 (Online)
Industrial Engineering & Management Systems Vol.18 No.3 pp.577-590
DOI : https://doi.org/10.7232/iems.2019.18.3.577

Threats of Changing Technology and Increasing Climate Variations: An Empirical Study of Business Opportunities and Challenges by KSA Firms

Divya Rana*, Fathimunisa Begam Afsar Hanfy
College of Administration and Finance, Department of Business Administration, Saudi Electronic University, Riyadh, Kingdom of Saudi Arabia
Department of Accounting, Saudi Electronic University, Riyadh, Kingdom of Saudi Arabia
Corresponding Author, E-mail: d.rana@seu.edu.sa
June 17, 2019 June 21, 2019 June 24, 2019

ABSTRACT


There has been an increase in demands where businesses are now required to respond to the threat of changing technology and the gradual increase in climatic variations, on the basis of the influential position that businesses are known to enjoy within the global community. If businesses are able to integrate people, technology, strategy and procedures while implementing initiatives that respond to climatic changes, it would result in creation of value in the long-term, which is a powerful too. However, there is a need to understand the threats that are presented by changing technology and climatic variations, which is the key focus of this research. The objective was to identify the business opportunities and challenges faced by businesses in KSA in the face of changing technology and climate change and whether there was an association between the two. The research adopted a quantitative methodology where the findings revealed that climatic variations can substantially impact businesses in terms of financial reporting, organizational reputation, legal responsibilities and supply chain and operations. It also found that business performance was also positively influenced by changing technology. The findings also revealed that changes in technology could also positive influence climatic variations. Thus, it can be concluded that changing technology and climatic variations bright forth substantial risks that could present opportunities as well as significant challenges for businesses operating in KSA.



초록


    1. INTRODUCTION

    The risks of climate change are reshaping the business environment for corporations around the globe. The direct impact of climate change along with the actions that government take to mitigate these impacts will confront companies with complex and unfamiliar challenges. Today, forward looking business in developing and industrialized countries are experimenting with innovative responses to these challenges, working to protect both profitability and the environment (Begg et al., 2005). The idea of sustainable development materialized at the Rio summit Agenda which integrates the principles and imperative worldwide for sustainable development. The business and companies are the key players in the implementation Kyoto protocol and therefore firms have to look beyond their core business activities and make important contribution to reducing greenhouse gas emission through innovation and the development of new technologies (Sullivan, 2017;Alpeisso et al., 2018).

    Therefore, it is imperative to emphasize on every target that focuses on reducing emission of greenhouse gases, production of renewable energy and achieve energy efficiency, keeping in mind the impact it would have on the industry and the business. This can help to ensure a transition which is table and does not make a negative impact on the organizational competitiveness. It should also be ensured that there is no obligatory trade-off between reversing the impact of climatic variations and fundamentally changing the lifestyle of people or sacrificing entire sectors from the industry. Economic data pertaining to the past two decades clearly indicate that there is compatibility in terms of economic growth and low carbon emission in Europe (European Commission, 2017). The objective for an economy that is greener and more sustainable could also be viewed as a scope for new economic opportunities. Within several regions of the world, it has been observed that there has been a substantial growth in terms of new employment opportunities which indicates thriving business practices. But, creation of jobs is only one facet. Extreme events that are climate related like tropical storms, extended droughts or floods could cause substantial losses. Business organizations that usually tend to depend on investments in the long-term are more prone to experience wider impacts as the outcomes from climate changes tends to grow over the period of time. Therefore, industry sectors like real estates have more scope to be more impacted by variations in the climate (Rincon-Flores et al., 2018;Al-Khalifah, 2018;Mendonça and Andrade, 2018).

    In the context of real energy challenges, Kingdom of Saudi Arabia has achieved a balance in this regard. The Kingdom of Saudi Arabia is dedicated to the concept of free trade based on competition. There are no foreign exchange controls, quantitative restrictions or tariff barriers. The focus of this study is to describe the climate change influenced on selected sectors in Saudi Arabia and to examine the level of organisational responses towards climate change. In specific, the objectives of the study are to look at the impact of climate variation on the business. Secondly, the study also examines the impact of new technologies on the business and finally the study examines whether both climate variation and new technology has shown to influence or hinder the KSA business performance.

    2. THEORY AND HYPOTHESES

    For instance, the study by Seles et al. (2018) identified and analysed challenges and opportunities that the climate crisis presents for organisation and implications of big data management using structured literature review. The review revealed that climate crisis tends to improve business performance (environment, financial and operational) and also generate new business. However, the review identified few challenges related to the inefficiency of governmental and regulatory support and an increase cost.

    Singh and El-Kassar (2019) investigated the extent to which green HRM practices influence the integration of big data technologies with process thereby enhance the relationship between green SCM and its influence on sustainable performance using dynamic capability theory. The survey findings confirmed the influence of big data driven strategies on the growth of business. On a similar line Singh et al. (2018) proposed a novel framework based on big data cloud computing technology for ecofriendly supplier selection process. Fuzzy AHP, DEMATEL and TOPSIS method are employed to make an optimum trade-off between the conventional quality attributes and carbon footprint generated in farms to select the most appropriate supplier. The study via the amalgamation of big data, operations research and ICT mitigated the carbon footprint of beef products.

    Based on the 2008 carbon disclosure project (CDP) database, the Backman et al. (2017) evaluated the firm level climate strategies for 552 companies from North America and Europe. The findings indicated that European firms perform better than North America in terms of investment made in governance, information management, systems and technology to develop capabilities in climate change impact mitigation.

    Studies conducted in the past have determined several strategic and stimulating drivers that might eventually enable organizations to take climatic changes into account while formulating strategies to deal with such changes. Ethical motivations or robust personal values might for example offer a deep encouragement for actions that could be deemed environmentally responsible, particularly when it is associated with key actors (Aguinis and Glavas, 2012). A large number of organizations nonetheless, tend to adopt an approach which is rather instrumental with regards to climate change challenges. This would comprise of pressure from external stakeholders, innovative business opportunities and technological innovation to tackle climatic challenges (Duraiappah, 2006).

    The objectives behind decisions made by organizations which eventually make an impact on their strategic goals pertaining to what organizations intend to achieve, that would in turn influence the extent of their actions (Dixon and Challies, 2015). At the same time, actors that are motivated intrinsically observe that actions that are environmentally responsible were rewarding on the whole, while considerations those that were spurred on the basis of economic opportunities would be restricted to actions that made sense from an economic perspective while offering competitive benefits. Enhancement in waste management for example is of value as it lowers the cost of production on the whole and ‘green marketing’ could also be instrumental in drawing interested investors, consumers or employees (Dixon and Challies, 2015;Ahmadi et al., 2018). In the absence of these kind of economic co-advantages, actions that are environmentally responsible might not be pursued. Another aspect that offers encouragement can be found within the organization’s external environment, in expectations of stakeholders and within legislations. Organizations that are fundamentally stimulated by worries about social legitimacy and license for operating would generally adopt strategies that are reactive with a view to satiate expectations of such kind. Concerns associated with climatic changes then become an aspect of the organization’s risk management process and at the same time, behaviour which is environmentally responsible tends to function as a medium to acquire access to business opportunities and resources, develop legitimacy and credibility with significant stakeholders or in order to circumvent costly sanctions in future. Though all the said three motives might eventually result in actions that are environmentally responsible, there might be variations in the actual behaviour and strategic decisions (Sharif and Butt, 2017).

    Bocij et al. (2008) on the other hand is of the opinion that technology has to a large extent brought about a revolution in an extensive array of functions which also comprises of business functions, external monitoring of the environment and communication between partners. Strategic goals which are clear along with commitment are some of the ground rules to ensure an improvement in business performance by leveraging the potential of information technology (Evans and Wurster, 1997). Porter and Millar (1985) also adds that information technologies can play an instrumental role in extending robust tactical and strategic tools for organizations which if applied in the proper manner and utilized could result in extensive benefits in terms of boosting and reinforcing organizational competitiveness. Information communication technology could prove to be a medium through which communication and information or knowledge exchange could be facilitated between diverse functions and departments within an organization. In this vein, information technology could play the role of an enhancer of collaboration and also act as a tool for networking between customers, employees and partners as it tends to eradicate the restrictions within realtime communication and the process of information sharing which is effective (Morton, 1991).

    Al-Ammary and Hamad (2012) is of the opinion that information technology can be instrumental in enabling organizations to innovate by fusing innovative technologies with business as well as society thereby facilitating the discovery as well as creation of new knowledge. As a matter of fact, organizations are utilizing information technology to augment performance, encourage employees, facilitate communication, enhance market dynamics, improve competitiveness and reposition the organizations at higher position as compared to its competitors thereby allowing them to foray into new markets.

    3. METHODS

    3.1 Survey and Data Collection

    Data was collected using surveys where questionnaires were distributed to 400 respondents. Out of the 400 respondents, 300 fully-filled questionnaires were received and included for the analysis purpose.

    3.2 Measures

    4. DATA ANALYSIS

    4.1 Outer Model Analysis

    Initially, the internal consistency of the data was checked through reliability analysis. Frequencies were evaluated in each demographical variables of the questionnaire. Correlation analysis was achieved to measure the relationship between the factors. The association between the variables were tested by linear regression.

    Table 1 depicts the distribution of personal information of the participants. The majority, 87.7% of the participants were male. Similarly, 27.3% of the participants belong to the age group between 36 and 45 years. The majority, 72.3% were got married, and 29.3% of the participants have done high school. Maximum 29% of the firms have 101-150 numbers of employees. Majority 38.3% of the participants have more than 5 years of experience.

    Majority, 27.3% of the participants stated that customers/ clients are the biggest security risk to the organization, 23.3% of the participants stated that moderately vulnerable is business to insider threats, and 66% stated that climate variation has an impact on business.

    The reliability analysis for all factors is depicted in Table 2. Cronbach’s alpha values range between 0.979 and 0.988, which specified that strong internal reliability occurs among all factor.

    The normality test by using the Shapiro-Wilk Test and Kolmogorov-Smirnov Test is presented in Table 3. The key benefits of the Shapiro-Wilk Test are that it can be used for both small (less than 50) and large sample sizes (above 2000). If the p-value is higher than 0.05, the data is considered to be normal. If the (p<0.05), the data is considered to deviate from a normal distribution. From the above results, the p-values for all the factors are greater than 0.05, but the sample size is above 50. So we might conclude that the data is normal.

    The thirty-seven statements are taken into account in factor analysis. Entire statements are condensed into 3 factors. The 3 factors are climate variation, new technology and business performance (Table 4).

    Confirmatory Factor Analysis (CFA) first order of new technology is depicted in Figure 1. The factor new technology has eight statements. The statements are represented as NT1, NT2, NT3, NT4, NT5, NT6, NT7 and NT8. Table 6

    Confirmatory Factor Analysis (CFA) first order of business performance is depicted in Figure 2. The factor business performance has fourteen statements. The statements are represented as BP1, BP2, BP3, BP4, BP5, BP6, BP7, BP8, BP9, BP10, BP11, BP12, BP13 and BP14.

    The hypothetical interdependence between one factor (Business Performance) structural equation modelling was used shows in Table 7. The fit indices reveal a model is a good fit suitable to be significant at the p > 0.05 (Table 8).

    The model is fit was acceptable representation of the sample data (χ2 (54) = 82.978, NFI (Normed Fit Index) = 0.994; IFI (Incremental fit index) = 0.998 which is greater than the 0.90 criteria as suggested by (Byrne, 1994) and 0.95 Schumacker and Lomax (2004). Similarly, CFI = 0.998, GFI = 0.960, RFI = 0.990 and RMR (Root Mean Square Residuals) = 0.008, values are lower the 0.08 critical value (Steiger, 1989) (Table 12). Table 9, 10, 11

    Confirmatory Factor Analysis (CFA) first order of climate variation is depicted in Figure 3. The factor climate variation has fifteen statements. The statements are represented as CV1, CV2, CV3, CV4, CV5, CV6, CV7, CV8, CV9, CV10, CV11, CV12, CV13, CV14 and CV15.

    Table 9 depicts the hypothetical interdependence between one factor (Climate Variation). Structural equation modelling was used. The fit indices reveal a model is a good fit and suitable are found to be significant at the p>0.05 (Table 10).

    The model is fit was acceptable representation of the sample data (χ2 (50) = 1028.430, NFI (Normed Fit Index) = 0.926; IFI (Incremental fit index) = 0.930 which is graater than the 0.90 criteria as suggested by Byrne (1994) and 0.95 Schumacker and Lomax (2004). Similarly, CFI = 0.929, GFI = 0.942, RFI = 0.845 and RMR (Root Mean Square Residuals) =0.036, values are lower the 0.08 critical value (Steiger, 1989) (Table 14).

    • Objective 1: To recognize the new technology existing in emerging businesses across KSA

    The hypothetical interdependence between one factor (new technology) structural equation modelling was used is revealed in table 5. The fit indices reveal a model is suitable for further analysis are found to be significant at the p > 0.05 (Table 6).

    The model is fit was acceptable representation of the sample data (χ2 (1) = 2.539, NFI (Normed Fit Index) =1.000; IFI (Incremental fit index) = 1.000 which is much greater than the 0.90 criteria as suggested by Byrne (1994) and 0.95 Schumacker and Lomax (2004). Similarly, CFI = 1.000, GFI = 0.998, RFI = 0.988 and RMR (Root Mean Square Residuals) = 0.001, values are lower the 0.08 critical value Steiger (1989) (Table 10).

    Table 13 depicts the association between new technology and business performance; structural equation modelling was used. The model fit, which was evaluated using global fit (seven different fit indices). The fit indices reveal a model is a good fit and suitable are found to be significant at the p < 0.05 (Table 14).

    The model is fit was acceptable representation of the sample data (χ2 (8) = 23.072, NFI (Normed Fit Index) = 0.984; IFI (Incremental fit index) = 0.998 which is greater than the 0.90 criteria as suggested by Byrne (1994) and 0.95 Schumacker and Lomax (2004). Similarly, CFI = 0.998, GFI = 0.984, RFI = 0.983 and RMR (Root Mean Square Residuals) = 0.014, values are lower the 0.08 critical value (Steiger, 1989).

    • Objective 2: To identify the impact of frequent threats of new technology in the emerging businesses across KSA

    Hypotheses:

    • H01: There is no significant impact of new technology on business performance

    • H11: There is a significant impact of new technology on business performance

    Table 11 depicts the influence of New Technology on Business Performance. The significance values of New Technology (β = 0.713, p < 0.01) specified that positively influence on Business Performance. In addition, the R-square value (0.281) revealed that 28% of Business Performance changed due to the effect of New Technology.

    • H02: There is no significant impact of new technology on climate variation

    • H12: There is a significant impact of new technology on climate variation

    Table 12 depicts the influence of New Technology on Climate Variation. The significance values of New Technology (β = 0.577, p < 0.01) specified that positively influence on Climate Variation. In addition, the R-square value (0.281) revealed that 39% of New Technology changed due to the effect of Climate Variation.

    Association between new technology and business performance, structural equation modelling was used in the Figure 4. In the model new technology is dependent variable and business performance is independent variable.

    Association between new technology and climate variation, structural equation modelling was used in the Figure 5. In the model new technology is dependent variable and climate variation is independent variable

    Table 15 depicts the association between new technology and climate variation; structural equation modelling was used. The model fit, which was evaluated using global fit (seven different fit indices). The fit indices reveal a model is a good fit and suitable are found to be significant at the p<0.05 (Table 16).

    The model is fit was acceptable representation of the sample data (χ2 (8) = 40.106, NFI (Normed Fit Index) =0.994; IFI (Incremental fit index) = 0.995 which is greater than the 0.90 criteria as suggested by Byrne (1994) and 0.95 Schumacker and Lomax (2004) (Table 16). Similarly, CFI = 0.995, GFI = 0.973, RFI = 0.971 and RMR (Root Mean Square Residuals) =0.020, values are lower the 0.08 critical value (Steiger, 1989).

    • Objective 3: To analyse the climate variation that affects the technology in the emerging

    Businesses

    • H03: There is no significant relationship between climate variations, new technology and business performance

    • H13: There is a significant relationship between climate variations, new technology and business performance

    Table 17 depicts the relationship between climate variation, new technology and business performance. The above findings revealed that Climate Variation (r = 0.474) and New Technology (r = 0.530) are a positive relationships with business performance. Hence, there is a relationship between climate variation, new technology and business performance.

    Table 18 depicts the influence of New Technology on Climate Variation. In step regression method, the significance values of Climate Variation (β = 0.688, p < 0.01) stated that positively influence on Business Performance. In addition, the R-square value (0.224) revealed that 24% of Business Performance changed due to the effect of Climate Variation. In step two methods, new technology (β = 0.516) and Climate Variation (β = 0.340, p < 0.01) stated that positively influence on Business Performance, and also R-square value (0.315) revealed that 32% of Business Performance changed due to the effect of new technology and climate variation.

    Figure 6 depicts the SEM model of climate variation, new technology and business performance structural equation modelling was used.

    Table 19 depicts the SEM model of climate variation, new technology and business performance. The model is good, which was measured using global fit (seven different fit indices). The fit indices reveal a model is a good fit and suitable are found to be significant at the p<0.05 (Table 20).

    The model is fit was acceptable representation of the sample data (χ2 (1) = 14.310, NFI (Normed Fit Index) = 0.945; IFI (Incremental fit index) = 0.949 which is greater than the 0.90 criteria as suggested by Byrne (1994) and 0.95 Schumacker and Lomax (2004) (Table 20). Similarly, CFI = 0.948, GFI = 0.970, RFI = 0.853 and RMR (Root Mean Square Residuals) =0.041, values are lower the 0.08 critical value (Steiger, 1989).

    5. DISCUSSION

    Continuous crises in the economy and the progressively advancing competition which has been an outcome specifically of market globalization is eventually causing a never before witness resource rationalization. Enhancement in productivity has therefore emerged to be a matter of grave concern for all organizations, public as well as private in all parts of the globe, including organizations in KSA. At the same time there has been an increment in the rate at which technological developments are occurring and is largely emerging as a major tool for organizations to tackle this challenge (Wilburn and Wilburn, 2018). This is clearly evidenced by large number of nations have been investing huge quantum of money in executing information systems. Nonetheless, technologies are known to offer several advantages, particularly with regards to offering improvements in productivity but these would hinge largely on how organizations incorporate technology within their organizations and how technologies align with other parameters.

    Similarly, variations in the climate is not only a lasting but a substantial change in terms of how patterns of weather have been statistically distributed over a period of time which ranges from several decades to several millions of years. Extremities in climate which is evident through climatic anomalies like earthquakes, floods, hurricanes etc., also substantially impact all businesses and business performance. The reputation of organizations, their legal responsibilities, financial reporting, regulatory obligations, supply chains and operations might be impacted (Deepmala, 2014). Change in climatic conditions locally as well as globally, the regularity and extremity in terms of weather conditions and water availability can directly make an impact on the risk profiles of organizations and in certain instances, the organization’s strategic positioning (Henderson et al., 2018). In view of these factors, this research intended to identify whether threats presented by changing technology and increment in climatic variations had any impact on business performance in KSA.

    The findings from this research indicated that business performance was positively influenced by new technology. This finding resonates with the findings presented by Chui et al. (2017) which reveal that technology changes could offer substantial value which is unrelated to substitution of labour and facilitates organizations to seek innovative ways to comprehend customer preferences, enhance their organizational operations with the help of tools related to predictive maintenance, streamline the documentation process and also respond in a prompt manner to climatic variations that can impact products and its delivery to customers. Nonetheless, the authors also add that deriving value through technological changes would often involve a redesign of the whole procedure and cannot be done by applying new technology to individual components within the procedure. The authors also warn that leaders of businesses also need to consistently keep track of new technologies being adopted by competitors in order to make sure that disruptive utilization of any new technology does not render the existing business model obsolete.

    The findings from this research also revealed that new technology positively influenced variation in climate. This finding also matches with the findings presented by previous researchers. According to Meera et al. (2004) information and communication technology (ICT) based applications are also known to utilize Geographic Information Systems (GIS). These applications include; Open Risk Data Initiative (Open RDI). The Open RDI is particularly utilized to lower the impact of disaster across nations around the world by motivating them to open their disaster related risk information. Technologies of GIS like thematic maps, satellite imagery and data which are geospatial play a major part in disaster risk management. The domains that are receiving urgent attention comprise of monitoring and management, information assessment pertaining to natural resources, environmental planning, development of watershed, land use planning and urban services.

    Lastly, this particular research also revealed that any variations in climate had the propensity to influence business performance. The influence of climate change on business performance however, can either be positive or negative as is evidenced by the paper presented by Henderson et al. (2018). According to the authors, variations in climate can throw up opportunities as well as wide-ranging threats for businesses. The very imminent impact of variations in climate have been known to threaten the overall viability of current businesses in the domain of construction and infrastructure and agriculture. However, changes in climatic conditions are also known to present substantial opportunities. For instance, it has been found that around 45% of consumers have no qualms about paying higher rates to buy products from organizations that are known to be environmentally friendly. Also, the quantum of people who are open to pay premium prices for products that are environment friendly is more within younger customers. Investments in the domain of technologies for sustainable energies are also known to present organizations with opportunities for cost saving. For instance, it has been found that 25% of operations in Wal-Mart is powered through renewable energy and the organization also proclaims that over a period of ten years they were able to reduce their use of energy by 20%, which lead to savings of around $1 billion (Carter and Jayachandran, 2012). In the Kingdom of Saudi Arabia, since the economy is driven by oil and construction business, and the fact that they experience extreme weathers, any change in climatic conditions can be countered with appropriate technology which can eventually influence business performance.

    6. Conclusion

    To conclude, variations in climate and technology present ample risks which in turn offer opportunities as well as substantial challenges to organizations within KSA. Variations in climate and new technology are proving to be a vital factor that determines the scope of an organization to ensure sustainability in terms of high performance and generate long-term value. The business landscape within KSA is being moulded by a variety of significant stakeholders owing to issues in climatic variations and adoption of new technologies. While new technology is required it can also prove to be a threat if not implemented or adapted appropriately. Similarly, changing climate can also be a threat but it also presents opportunities as it is evident in the above section. For organizations in KSA or any region to effectively mitigate and manage the variations in climate, it is imperative that they adopt new technology. Organizations that are synchronized with such changes and those who respond to such variations in a proactive and timely manner will be in a position to progress towards a high performance in their business in a sustainable manner as compared to their competitors.

    6.1 Limitations

    This research intended to evaluate the impact of new technology and climatic variations on business opportunities and challenges with specific reference to the Kingdom of Saudi Arabia. The research however exclusively focused only on KSA hence there is definitely a need to conduct further research on the similar lines while taking into considerations several other nations too. This will help to identify whether climatic variations and new technology did present new opportunities or challenges for business and strategies to tackle it.

    ACKNOWLEDGEMENT

    We would like to thank Deanship of Scientific Research at Saudi Electronic University, Kingdom of SaudiArabia for the financial grant no. (7642-HS-2019-1-1-S) received in conducting this research.

    Figure

    IEMS-18-3-577_F1.gif

    CFA first order of new technology.

    IEMS-18-3-577_F2.gif

    CFA first order of business performance.

    IEMS-18-3-577_F3.gif

    CFA first order of climate variation.

    IEMS-18-3-577_F4.gif

    Association between new technology and business performance.

    IEMS-18-3-577_F5.gif

    Association between new technology and climate variation.

    IEMS-18-3-577_F6.gif

    SEM model of climate variation, new technology and business performance.

    Table

    Frequency of personal information

    Reliability analysis

    Test of normality

    Factor analysis

    CFA first order of new technology

    Model fit summary

    CFA first order of business performance

    Model fit summary

    CFA first order of climate variation

    Model fit summary

    Association between new technology and business performance

    Association between new technology and climate variation

    Association between new technology and business performance

    Model fit summary

    Association between new technology and climate variation

    Model fit summary

    Relationship between climate variation, new technology and business performance

    Association between climate variation, new technology and business performance

    SEM model of climate variation, new technology and business performance

    Model fit summary

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