1. Introduction
The development of service innovations follows a service innovation pattern, and product innovations follow a product innovation pattern with the aim of serving consumers including new methods of doing it through technologies or procedures. As a consequence of the advent of modern ideas, entirely new types of customer services have been created (Lee & Xuan, 2019; Jawabreh, 2020; Chowdhury et al., 2020). Service innovation can be used to design services that address previously unmet customer needs and open up new business areas, sustainably differentiate the company from the competition and increase customer loyalty. Restaurants must continue to innovate and follow effective business strategies that enable them to succeed in ever-changing market environments. Accordingly, businesses will continue to confront new regulations and industry trends, as they are reconsidering policies and procedures. Noting no business is unaffected by those positive traits. For restaurants to be profitable, they must be able to anticipate and respond to the needs of the consumers.
The hospitality and tourism sectors do use “innovation” and “hype” very often but are behind the times as it comes to newer technology. Many studies have researched about innovation, however, most of that has been related to product innovation. Fusion innovation, co-fetching, invisible innovation, and service innovation are other fields to explore.
Restaurants can begin to modernize their approach. As customers change their lifestyles, businesses must be flexible and ready to react. Most changes occur in the blink of an eye and go unnoticed. The current population evolution, new consumer demands, and the economic downturn have all had an effect on these developments. According to the research, the majority of retail firms fail to maximize their profits The key aim of the research is to discover the mindset of restaurant management, as well as the views on new developments in the restaurant industry technologies.
Several directions in business can lead to innovation, one of which is to integrate activities in novel ways (Nguyen, 2020; Sumiati, 2020). An organization must assess its capabilities, such as finances, technology, and government policy to determine its path of growth. The types of inventions to be found in this study are commodity, operation, administration, as well as supply chain innovations. (Masadeh et al., 2019). Marketing a manifestation of creativity in the hospitality industry. New and different methods of doing business have transformed the hospitality and travel industries. In today’s world, online forums are creating a valuable resource for consumers by making it possible for them to share, debate, and develop their ideas. At certain hotels, visitors use the new gadgets in the lobby to create dinner arrangements or engage with each other in the lobby using their smart devices.
Jordan’s GDP decreased by 2.2% in the third quarter of 2020, down from a historic 3.6% decline the year before. The hotel, restaurant, transportation, warehousing, and recreational vehicle industries are all worst affected by the coronavirus outbreak and saw a decline by –5.3% when compared to –3.2% in 2009 (–3.2% vs –5.3%). Hotel and restaurant revenues in Jordan amounted to $293 million in 2009. This is an increase from the previous figure of 260.6 billion JD in 2008. Hotels and Restaurants GDP (gross output) was reported at 542.500 JD mn in 2009. This records an increase from the previous number of 506.900 JD mn for 2008. Hotels and Restaurants data is updated yearly, averaging 125.450 JD mn from Dec 1976 to 2009. The data reached an all-time high of 542.500 JOD mn in 2009 and a record low of 39.900 JOD mn in 1976. Department of Statistics compiles information on hotels and restaurants. Value-added in wholesale, retail exchange, and tourism increased by 2, 976 percent in 2019 in Jordan valuing 35.9 million and maintaining an overall annual rise of 10.25%, (CEIC, 2020).
In this restaurant analysis, the empirical verification of the internal network concept of social capital (ISC) is extended to social capital (K) and new product development (N) for the first time. This is the first research exploring the interaction between ISC and NPI, and the impact of both on the classification of restaurants in Jordan.
2. Literature Review
Hospitality industries are investing a lot of money on technical systems and processes to support employees’ knowledge and productivity (Nguyen & Mohamed 2011; Park et al., 2012). Many businesses and organizations state that being aware of customer expectations is a key component of long-term success (Grant 1996; Davenport & Prusak 1998). Organizations must develop an organizational culture because a successful organizational culture brings together the people in the company and keeps them aligned. The culture at an organization sets expectations for how people behave and work together, and how well they function as a team (Argote et al., 2003).
By way of contrast, in Jordan, more attention is paid to developing new methods and new processes. A range of factors influences organizational creativity. One of the best ways to gather new knowledge is to provide employees with more hands-on activities through which they can take part in the process of creating it. More understanding is created by interactions with others and this kind of experience and fresh information strengthens the organizational framework. As a result, having the capacity to change can affect overall company creativity in the workplace. Openness to structural change has become a constant over the last few years. The organizational transition may lead to costly consequences, including decreased organizational effectiveness, reduced recruitment, and reduced attendance for organizations.
Openness to change is seen as a necessary trait for successful leaders. The main objective of knowledge management is to create awareness and then share it. (Ottenbacher & Harrington, 2009). The flow of information in an organization is often dependent on people’s willingness to pass along their knowledge. Knowledge management is the process of creating, sharing, using, and managing the knowledge and information of an organization. It refers to a multidisciplinary approach to achieve organizational objectives by making the best use of knowledge (Gibbert & Krause, 2002; Muhammad et al., 2014). Knowledge will only flow from person to person if the person within the company is motivated to do so (Davenport et al., 1998).
Research has identified several impediments to human and business knowledge sharing. Knowledge sharing is being recognized as central to new knowledge creation, creativity, and organizational learning. Implementing organizational goals is concerned with sharing of knowledge. Organizational wellbeing occurs as a result of sharing of knowledge.
Evidence from several experiments has shown that the ability and motivation of employees to communicate with an organization related to the acts they do on the job (Cabrera et al., 2006; Chen et al., 2009; Reychav & Weisberg 2010). The primary issue studied by Chen and Kinsuk (2009) was the variables that influence knowledge-sharing behavior in a simulated setting. Participants who displayed more positive attitudes showed greater interest in exchanging details, perhaps because of it. Reychav and Weisberg (2010) conducted a study of 278 employees in Israel’s telecom industry to better understand the role that commitment plays in the actual exchange of information. Employees were able to directly report their experiences as well as provide simple and subtle ways of exchanging facts and ideas.
If an employee’s ability to adapt is dependent on how he or she perceives changes, this could negatively impact a company’s creative process. If jobs are willing to be included in the knowledge production process, there would certainly be fresh talent (Tang & Marinova, 2020). The current investigation is intended to overcome aversions to exchanging details as part of a collective cognitive theory (SCT) (Bandura, 1986). Humans may be understood as individual, behavioral, and environmental, as well as a whole. Previous research by Guan et al. (2018) and Yan et al. (2016) had shown that human factors such as community knowledge and an organizational structure that promotes collaboration are essential to information sharing. Previous researchers tried to understand numerous knowledge-sharing influences, particularly in the context of virtual communities that have been overlooked. They found that online commerce has a large effect on both explicit and implied information exchanges (Ma & Agarawal, 2007). Members of any organization are more likely to use IT technology if they are interested, engaged, well informed, and competent (Ruppel & Harrington, 2001; Shao et al., 2016; Bock et al., 2005; Yu et al., 2010; Park et al., 2018). Recent studies show emplo yees’ intent to contribute significantly to actual knowledge sharing in a company (Cabrera et al., 2006; Chen et al., 2009; Reychav & Weisberg, 2010).
3. Methodology
An analytical method was used to determine the direct and inverse correlations between variables Over 682 questionnaires were distributed, 62 were found to be inadequate because they had fewer than 3 responses each. The final study sample was 620. Personal data was gathered through a questionnaire sent in the mail and person. Only a few short answers were all that the survey respondents requested, but some wanted more information by phone or email. We constructed our questionnaire based on previous studies.
The data analysis was performed using SIMS and AMOS, Certain analyses were done to corroborate the data, as well as to test the model’s accuracy. Relative bias forecasts were tested using previously agreed-upon hypotheses. The research used a significance level of 0.05 in its calculations.
Table 1: Demographic Information
H1: Structural finance has a beneficial impact on new product innovation.
H2: Relational capital has a beneficial impact on new product innovation.
H3: Cognitive capital has a beneficial impact on new product innovation.
H4: Structural capital has a constructive impact on the intention to share information.
H5: Relational capital has a constructive impact on the intention to share knowledge.
H6: Cognitive capital has a beneficial impact on the intention to share knowledge.
H7: Knowledge Sharing Purpose has a beneficial impact on New Product Innovation.
H8: Knowledge Sharing Purpose mediates the relation between structural resources and new product innovation.
H9: Knowledge Sharing Purpose mediates the connection between Relational Resources and New Product Innovation.
H10: Knowledge Sharing Purpose mediates the connection between Cognitive Resources and New Product Innovation.
3.1. Sample and Data
Males comprised 68.23% of the sample. 29.84% were in the age group of 51–60 years and 11.94% were less than 31 years. 59.35% had a bachelor degree and only 8.55 had a Postgraduate degree.
3.2. Measurement Model
Confirmatory factor analysis (CFA) is used to determine how well the model fits the data. Items have not been excluded from review based on the CFA. Table 2 reveals a close correspondence between the model and the results (χ2 = 1.98; IFI:F; TL:CFI; SRM = 0.0; MSEA: 0.57). Cronbach’s alpha is a measure of internal consistency, that is, how closely related a set of items are as a group. It is considered to be a measure of scale reliability. A generally accepted rule is that α of 0.6–0.7 indicates an acceptable level of reliability. The Cronbach’s alpha value is greater than 0.6, which means all variables are reliable. Discriminant validity is demonstrated by evidence that measures of constructs that theoretically should not be highly related to each other are, in fact, not found to be highly correlated to each other. The average variance extracted has often been used to assess discriminant validity based on the following “rule of thumb”: the positive square root of the AVE for each of the latent variables should be higher than the highest correlation with any other latent variable (Hair et al, 2012). The square root of each estimate was larger than the corresponding r partial correlations. The chart above shows the validity of the build represented by the main diagonal line’s variable loading in Figure 1.
Table 2: Goodness of Fit Statistics
Figure 1: Conceptual Model
Convergent validity refers to how closely the new scale is related to other variables and other measures of the same construct. Not only should the construct correlate with related variables but it should not correlate with dissimilar, unrelated ones Convergent validity evaluation produces particularly Build validation in Figure 1. Factor loading is basically the correlation coefficient for the variable and factor. Factor loading shows the variance explained by the variable on that particular factor. As a rule of thumb, 0.5 or higher factor loading represents that the factor extracts sufficient variance from that variable. All factor loading values are above 0.50 (Hair et al., 2006).
Table 3: Correlation Coefficients and the Square Root of AVE (N = 344)
Notes: **p < 0.01, *p < 0.05.
4. Results
The structural model was examined in two stages. In the first Stage (direct effect), the effect on (SC → NPI) were not significant (p-value > 0.05, Confidence limits include zero) (see Table 4 and Figure 2), therefore H1 was not supported. However, the effect of (RC → NPI), (CC → NPI) were significant (p-value < 0.05, Confidence limits do not include zero), hence, hypotheses 2 and 3 were supported.
Table 4: Bias-corrected Bootstrap Results (Direct Effect)
Figure 2: Standardized Parameter Estimate
Hypotheses 4, 5, and 6 (Table 5) show that (p-value < 0.05, Confidence limits do not include zero) so these hypotheses were supported. As for the effect of the mediator (KSI) on the dependent variable (NPI) (p-value < 0.05, Confidence limits do not include zero), hence, hypothesis 7 was supported.
Table 5: Mediation Effects Result
As seen in Table 5, the indirect influence, as well as the difference between SD and SCIs, cannot be disregarded (p < 0.05, significantly between SDI and SCIs). Since the direct impact of KSI as a moderator (SC to NPI) did not produce any results, hypothesis 8 was supported. Although the direct and indirect effects (RC → NPI, but only part of the hypothesis) were important as indicated, the partial impact (CC → NPI) was supported.
5. Discussion and Conclusion
When it comes to restaurants, the emphasis is on consumers and the creation of a new approach. Often contemporary customers want fast response and service that is customized to meet their specific needs. Businesses have to grow and profit by introducing new operations, also referred to as “forward and backward integration, ”, and then connect them in new ways.
Many hospitality organizations have the newest consumer gadgets such that visitors can check-in at the front desk to see what is available in the lobby and program their dining and other facilities beforehand. The aim of the study is to discover the thoughts that hospitality firms have on innovation so that they can learn how to keep their status in the industry when adjusting to changes. Currently, there are also areas on which further testing still needs to be done.
In Jordan, creativity and advanced techniques are placed above everything others. Opening one’s mind and accepting new ideas and different points of view are believed to be crucial for effective leadership to effectively deal with resistance to change and propel it along, and to ensure success. A company must be aware of its workforce’s state of mind. Since the willingness of workers to adjust has implications for the overall creativity of the workforce, employees must be educated. Companies must exchange knowledge with team members. Establishing a training and development policy is a way of honoring employees’ achievements, as well as their work process will be improved (Cho et al., 2017).
One of the main functions of organizations is to build and sustain a community-friendly environment in which employees can freely share information, which also includes knowledge management programs that are designed to promote the exchange of knowledge. Often, individuals will know very little about what’s transpiring between organizational participants; this may restrict the flow of information and thus have a restraining effect on them and others from getting the full picture of the organization’s activity and results. Most modern corporations are vulnerable to structural change in the sense that they must face external and internal challenges as well as that they are capable of shifting toward a different system to succeed. The more an organization is unable to adapt, the more costly would be the consequences, particularly if the cost of employee turnover and success is higher. As new knowledge, creation of technology in the market becomes a must for corporations, so is the sharing of information vital to business. A free flow of knowledge into the company would allow employees to acquire and improve their skills, while fresh talent would most certainly emerge (Nonaka, 1994).
The research sample was restricted to Aqaba in Jordan, who were participants of a single online Q&A group. More analysis is required to validate the generalizability of the observations of the research. To analyze how the social environment impacts information exchange, future studies may use empirical evidence. The research did not take into account population form, they report.
참고문헌
- Anderson, J. C., & Gerbing D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103, 411-423. https://doi.org/10.1037/0033-2909.103.3.411
- Argote, L., McEvily, B., & Reagans, R. (2003). Managing knowledge in organizations: An integrative framework and review of emerging themes. Management Science, 49(4), 571-582. https://doi.org/10.1287/mnsc.49.4.571.14424
- Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Englewood Cliffs, NJ: Prentice-Hall.
- Bock, G. W., Zmud, R. W., Kim, Y. G, & Lee, J. N. (2005). Behavioral intention formation in knowledge sharing: Examining the roles of extrinsic motivators, social-psychological forces, and organizational climate. MIS Quarterly, 29(1), 87-111. https://doi.org/10.2307/25148669
- Cabrera, A., Collins, W., & Salgado, J. (2006). Determinants of individual engagement in knowledge sharing.The International Journal of Human Resource Management, 17(2), 245-264. https://doi.org/10.1080/09585190500404614
- CEIC. (2020). GDP: Gross output: Jordan hotels and restaurants. https://www.ceicdata.com/en/jordan/gdp-gross-output-byindustry-current-price/gdp-gross-output-hotels-and-restaurants
- Chen, I. Y. L., Chen, N. S., & Kinshuk, R. (2009). Examining the factors influencing participants' knowledge sharing behavior in virtual learning communities. Educational Technology & Society, 12(1), 134-148. http://dblp.uni-trier.de/db/journals/ets/ets12.html#ChenCK09
- Cho, M., Bonn, M. A., & Han, S. J. (2020). Innovation ambidexterity: Balancing exploitation and exploration for startup and established restaurants and impacts upon performance. Industry and Innovation, 27(4), 340-362. https://doi.org/10.1080/13662716.2019.1633280
- Chowdhury, M., Prayag, G., Patwardhan, V., & Kumar, N. (2020). The impact of social capital and knowledge sharing intention on restaurants' new product development. International Journal of Contemporary Hospitality Management, 6(9), 45-58. https://doi.org/10.1108/IJCHM-04-2020-0345
- Davenport, T. H., & Prusak, L. (1998). Working knowledge: how organizations manage what they know. Boston, MA: Harvard Business School Press.
- Davenport, T., De-Long, W., & Beers, M. (1998). Successful knowledge management projects. Sloan Management Review, 39(2), 43-57. https://sloanreview.mit.edu/article/successfulknowledge-management-projects/
- Guan, T., Wang, L., Jin, J., & Song, X. (2018). Knowledge contribution behavior in online q&a communities: An empirical investigation. Computers in Human Behavior, 81, 137-147. https://doi.org/10.1016/j.chb.2017.12.023
- Grant, R. M. (1996). Toward a knowledge-based theory of the firm. Strategic Management Journal, 17, 109-122. https://doi.org/10.1002/smj.4250171110
- Gibbert, M., & Krause, H. (2002). Practice exchange in a best practice marketplace. (2nd ed.). Upper Saddle River, NJ: Prentice-Hall.
- Hair, J. F., Sarstedt, M., Ringle, C. M., & Mena, J. A. (2012). An assessment of the use of partial least squares structural equation modeling in marketing research. Journal of the Academy of Marketing Science, 40(3), 414-433. https://doi.org/10.1007/s11747-011-0261-6
- Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (2006). Multivariate data analysis (6th ed.). Upper Saddle River, NJ: Prentice-Hall.
- Jawabreh, O. (2020). Innovation management in hotels industry in Aqaba special economic zone authority: Hotel classification and administration as a moderator. GeoJournal of Tourism and Geosites, 32(4), 1362-1369. https://doi.org/10.30892/gtg.32425-581
- Lee, J. W., & Xuan, Y. (2019). Effects of technology and innovation management and total factor productivity on the economic growth of China. The Journal of Asian Finance, Economics, and Business, 6(2), 63-73. https://doi.org/10.13106/JAFEB.2019.VOL6.NO2.63
- Masadeh, R., Alananzeh, O., Jawabreh, O., Alhalabi, R., Syam, H., & Keswani, F. (2019). The association among employee's communication skills, image formation, and tourist behavior: Perceptions of hospitality management students in Jordan. International Journal of Culture, Tourism and Hospitality Research, 13(3), 257-272. https://doi.org/10.1108/ijcthr-02-2018-0028
- Muhammad, H., Shah, B., & Islam, Z. (2014). The impact of capital structure on firm performance: Evidence from Pakistan. Mountain Landscape Research Journal, 5(2), 13-20. https://doi.org/10.13106/JIDB.2014.VOL5.NO2.13
- Nguyen, T. N. (2020). The effect of bribery on firm innovation: An analysis of small and medium firms in Vietnam. The Journal of Asian Finance, Economics, and Business, 7(5), 259-268. https://doi.org/10.13106/JAFEB.2020.VOL7.NO5.259
- Nonaka, I. (1994). A dynamic theory of organizational knowledge creation. Organization Science, 5(1), 14-37. https://www.jstor.org/stable/2635068 https://doi.org/10.1287/orsc.5.1.14
- Nguyen, H. N., & Mohamed, S. (2011). Leadership behaviors, organizational culture and knowledge management practices: An empirical investigation. Journal of Management Development, 30(2), 206-221. https://doi.org/10.1108/02621711111105786
- Ottenbacher, M. C., & Harrington, R. J. (2009). The product innovation process of quick-service restaurant chains. International Journal of Contemporary Hospitality Management, 21(5), 523-541. https://doi.org/10.1108/09596110910967782
- Park, S. H., Cottingham, M., & Seo, W. J. (2018). The role of mega sports events and social capital: A study on the comparison of the perspectives of the Korean and American event-hosting communities, focusing on the theory of conflict. Mountain Landscape Research Journal, 9(9), 63-74. https://doi.org/10.13106/IJIDB.2018.VOL9.NO9.63
- Park, T., Saplan, C. V. J., & Jaegala, D. (2012). Predicting knowledge sharing intentions in the public sector: Comparing TAM with TPB. International Review of Public Administration, 17(2), 93-120. https://doi.org/10.1080/12294659.2012.10805229
- Pi, S. M., Chou, C. H., & Liao, H. L. (2013). A study of Facebook group members' knowledge sharing. Computers in Human Behavior, 29(5), 1971-1979. https://doi.org10.1016/j.chb.2013.04.019
- Reychav, I., & Weisberg, J. (2010). Bridging intention and behavior of knowledge sharing. Journal of Knowledge Management, 14(2), 285-300. https://doi.org/10.1108/13673271011032418
- Ruppel, C. P., & Harrington, S. J. (2001). Sharing knowledge through intranets: A study of organizational culture and intranet implementation. IEEE Transactions on Professional Communication, 44(1), 37-52. https://doi.org/10.1109/47.911131
- Shao, Z., Feng, Y., & Wang, T. (2016). Charismatic leadership and tacit knowledge sharing in the context of enterprise systems learning: The mediating effect of psychological safety climate and intrinsic motivation. Behaviour & Information Technology, 36(2), 194-208. https://doi.org/10.1080/0144929x.2016.1221461
- Sumiati, S. (2020). Improving small business performance: The role of entrepreneurial intensity and innovation. The Journal of Asian Finance, Economics, and Business, 7(10), 211-218. https://doi.org/10.13106/JAFEB.2020.VOL7.N10.211
- Tang, Y. E., & Marinova, D. (2020). When less is more: The downside of customer knowledge sharing in new product development teams. Journal of the Academy of Marketing Science, 48(2), 288-307. https://doi.org/10.1007/s11747-019-00646-w
- Yan, Z. J., Wang, T. M., Chen, M., & Zhang, H. (2016). Knowledge sharing in online health communities: A social exchange theory perspective. Information & Management, 53(5) 643-653. https://doi.org/10.1016/j.im.2016.02.001
- Yu, T. K., Lu, L. C., & Liu, T. F. (2010). Exploring factors that influence knowledge sharing behavior via weblogs. Computers in Human Behavior, 26(1), 32-41. https://doi.org/10.1016/j.chb.2009.08.002