Dinkum Journal of Economics and Managerial Innovations (DJEMI).

Publication History

Published: March 01, 2023

Identification

D-0039

Citation

Baah Lydia, Nyantakyi Tetteh, and Masud Kong, (2023). Consumers’ behavioral motives towards adoption of mobile commence in Ghana. Dinkum Journal of Economics and Managerial Innovations, 2(03):163-173.

Copyright

© 2023 DJEMI. All rights reserved

Consumers’ Behavioral Motives Towards Adoption of Mobile Commence in GhanaOriginal Article

Baah Lydia1, Nyantakyi Tetteh 2, and Masud Kong 3,*

  1. Central Business School, Central University Accra Ghana, Ghana; baah_lydia201@gmail.com
  2. Central Business School, Central University Accra Ghana, Ghana; Tetteh.n@gmail.com
  3. Central Business School, Central University Accra Ghana, Ghana; masud.kong@gmail.com

*             Correspondence: masud.kong@gmail.com

Abstract: Recent development and growth in the last few years in the mobile industry and the evolution of new and user-friendly mobiles have been found to bring drastic evolution in the lives of people, especially the students we are focusing on in this study This study analyzed how the system and service quality of mobile enterprise in the context of Ghana has been an intention for students in the continuity of its purchase The questionnaire developed includes 17 generic questions involving the variables that were taken for this study to be filed by N=450 respondents from Ghana The sample hence has been selected from a simple random sampling method Resultantly, the data was analyzed by the statistical software PLS-SEM, as the data was quantitative The results reflect the same as expected, saying that system, service quality, and satisfaction has major effect on continuous customer intention towards a mobile purchase in the presence of trust that has been developed since the customer went through the system, service, and satisfaction phases All the hypotheses gave significant values This study has proved a landmark for different contexts and could be used by different national and international mobile firms as a secondary source for their actual selling and further research prospects The study could not be generalized due to the lesser sample size, as it was time consuming The study does not involve concepts telling the scenarios that might differ in dealing with cross-cultural contexts requiring further research.

Keywords: system quality, service quality, continuous customer intention, trust, satisfaction

  1. INTRODUCTION

The use of mobile communication has brought a drastic change in mobile usage in Ghana  The applications of new communication technologies has pushed and introduced new usage of mobiles  Nowadays, sale purchase of products or services with mobile is increasing and attracting the intentions of researchers [1]  According to sources in the e-commerce market there will be millions Smartphone users in next few years  This will create a huge demand of mobile use and growth in telecom sector  According to mobile purchase has increased up to the expectations all over the world  It is important for mobile vendor to attain new customers but more important to retain the existing customers [2]  It has revealed that the cost to acquire a new user, is five times as compared to retaking the existing  While comparing online and offline commerce, because of vulnerability of mobile networks, the mobile commerce now involves greater uncertainty of risk  There is a distrust that exists, when it comes to mobile vendors and mobile payment system [3]  In context of Ghana, the adoption of mobile has not received wider purchase among consumers and the growth in the industry was far behind the expectation  Compared to entertaining applications like TV and Mobile music has been used much more than the purchase of mobile adoption rate representing transactional application [4]  As compared to cost they spent on developing and managing the system, the mobile purchase has been very unsatisfactory  Mobile vendors through the usage of hand-held devices, although could offer large number of advanced services but people who have purchased are not willing to use mobile device for shopping thus the growth in mobile purchase is comparatively slow [5]  The acquisition promoting of mobile purchase is an initial step for mobile vendors and all they need to do is to facilitate and retain the existing customers by assisting the existing purchase and let them continually make purchase [6]  It has been found out that the cost of attaining new customers is five times higher than the cost spent on existing users [7]  The Mobile Purchase Service has been a great part of investment and has been a great resource for mobile service providers, however the cost could not be recovered and profits could not be made which may let them discontinue the purchase and use when these also exist the  intense competition among different members [8]  There a few studies prevail about the mobile shopper’s behavior so there exists a gap that does not identify the factors that influence and affect the continuity of behavior  For understanding of initial adoption and the technology related to the acceptance of its purchase, it has not yet been a focus point for researchers  The primary objective of the study is  determine the system quality of mobile so that the mobile vendor could develop a trust on consumers  What if service quality of mobile significantly effects the trust of  consumer and look upon the level of satisfaction that tends to impel consumer for purchase or repurchase  It has also evaluated the effect of trust in testing the continuous intention of consumer

  1. LITERATURE REVIEW

Recent studies have shown the relationship between system quality and service quality with continuous customer intention, and with reference to this, the researchers have found few relationships that have significant effects [9].

2.1 Mobile Purchase

The commerce of mobile is growing all around the world very rapidly  Many researchers have defined “Mobile Commerce” in different ways and stated that mobile commerce is being used as wireless technology, assisting technological transactions, used as hand hold device, also used for the search of information [10], the performance of tasks for consumer B2B, Inter and Intra-enterprise connection and communication  In this study, the term Mobile Commence is said to be any transaction that is done for Paid purpose held over wireless channels  According to previous research in mobile purchase  This research elaborated that smart phone purchase is somehow related to mobile purchase [11]  Purchase of mobile has now become easy because of internet, customers use mobile to plan the pre-shopping activities (finding store hours and directions), and they are used for composing, modifying and placing orders to conduct purchase transactions online [12]  With the help of mobile devices without looking at time or location, comparing general purchase on internet, the purchase on mobile allows one to serve on internet without constraint of time, location, mobile network and devices  Based on location based services mobile service providers can get information about location  The information once taken could be related to information or service and could be used to provide relevant information or practical services to users [13]  Hence the internet in mobile could be utilized as retailers provided customized service pin pointing the location to interact with customers or consumer buying handsets  This has provided convenience and intern value to customers thus facilitated the adoption of mobile purchase [14]. This too contains uncertainty and risk due to lack of control and virtual potential opportunism. Mobile Encryption systems are not as intact as online encryption systems. This help to draw about consumer interest in concern about security of mobile while purchasing  They are concerned if mobile vendors could easily and effectively protect their personal information i-e privacy Security of payment [15].

2.2 Trust

Trust reflects a willingness to be vulnerable based on positive expectations toward another party’s behavior [16]. There are usually three types of beliefs that are included in the trust.

  1. Ability
  2. Integrity
  3. Benevolence

Here ability means that the vendors of mobile have enough skills and have gathered enough knowledge for the fulfillment of tasks [17]. Integrity means that those vendors know that their prime responsibility is not to deceive the customer, and they must keep the promise [18]. Benevolence means that while making mobiles, the vendors keep the interest of the consumer, not only their own benefits [19]. Because of the vulnerability of perception like distrust and payment systems of online commerce or mobile commerce have been found to be in greater risks or uncertainties compared to offline commerce [20]. Mobiles, due to their technological inputs, may sometime also get infected by trogon horses or viruses. Mobile purchase indeed is a subject of security and privacy concerns, thus including risk and mistrust as has been encountered through studies. Thus mobiles do not have tangible indicators for testing product quality   The buyers of mobile may also have to oversee if their accounts of credit cards and passwords can be transmitted or stored [21]  Mobile shoppers may have concern with privacy of location without consulting the users themselves  Due to the problem of privacy and security concerns, there is greater risk and perceived uncertainty and risk  This resultantly will have to build trust so as to facilitate or mitigate perceived risk; hence mobile could continually be used  Behavioral intention could then become an important determinant of “trust” [22]  Researchers suggested “privacy- Trust- behavioral intention model” for understanding electronic commerce in context of consumer behavior  The main and basic reason for most of the people for not conducting online shopping is that people mistrust transactions performed electronically  Researchers demonstrate that trust has always been a positive association with shopping of mobile [23].

2.3 Satisfaction

Through multiple interactions with mobile vendors, they developed a feeling of satisfaction. The usage of mobile is usually disconnected if the consumer of the direct user is not satisfied with the mobile vendor or disconnects its usage. Earlier studies have shown that satisfaction is positively associated with fewer behavior [24]

2.4 System Quality

The quality of the system is associated with connection, speed, visual appeal, ease of use and navigation when it comes to mobile system mobile networks and terminals have freed users from terminal and spectral constraints and enabled them to conduct ubiquitous purchase [25]  The appearing connection and communication has been affecting the trust of users while operating transaction in mobile  There are different mobile sites that users usually find difficult to use and due to this consumers feel that service providers are not capable enough to incorporate their service that led them to harm their quality [26]  A study in 2009 revealed that system quality had been affecting the trust of users in mobile banking  Mobile websites have been affected by quality of system  Consumers may feel discontent because of lack of involvement while operating the sites, this leads to the feeling of lack of control due to service might be taken abruptly [27]  This results in a decrease in perceived control and increased consumer frustration that would undetermined their experience with the mobile vendor  A poor quality of system can never satisfy users as they always are ready to accept the adoption of commerce system that satisfies them  Early researches had notified the effects of system quality on the satisfaction of the user of sites of mobile internet, the work of mobile in healthcare service   [28.

2.5 Service Quality

Reliability, responsiveness, personalization and assurance reflect the term “service quality”  Consumers however will never develop trust in them if the mobile vendors give unreliable services and provide slow response which fails to develop trust [29]  For example, if the consumer doesn’t get a timely answer about the queries of customers this tells them that the vendors of mobile are not capable enough to deal with certain information  So the quality of service has impact on consumer trust  The service quality has affected the trust of consumers and virtually traveling communities, which indicates the relation of service quality being positively related to service payment of mobile [30]  Moreover, online shopping satisfaction is positively associated with service quality  “Virtual Travel community” and SMS [31]  Consumer could present services as to develop the trust and this helps in attracting the customers so that they feel satisfaction and this leads to “repurchase” of product [32]  The following figure shows the framework of the present research model where system quality, service quality and satisfaction has an impact on trust where the trust has an impact on consumer continuous intention, which is being dependent variable  Following hypothesis has been tested in the study.

H1: System Quality has a direct relation with trust.

H2: Service quality has a direct relation with trust.

H3: Satisfaction has a direct relation with trust.

H4: Trust has a direct relation with continuous consumer intention.

 

 

Figure 01: Theoretical Framework

  1. MATERIALS AND METHODS

The data was collected by liker scale-based questionnaire consisting generic questions taken from different sources  The questions of system quality and service quality were adapted from, the questions for satisfaction were adapted from, the questions for trust were taken from and questionnaire for consumer continuous intention were adapted from  After selecting the questionnaire, we decided the sample size for our study  According to the Steven [33] the sample size for social science researches should be greater than 15 times from its predictor  In our research model  we have 5 predictors so according to this our sample size should be greater than 80  So we selected simple random sampling technique and collected the data from N=450 respondents who were student of university of engineering and technology  Partial least square based on structure equation modeling  method is used to analyzed and measure the research hypothesis  Variant of multiple regression can easily solved with PLS-SEM technique  PLS- SEM is a multivariate technique which can consider much comparison between many dependent and independent variables  Smart PLS version 3.0 is used to collect and analyzed data it was first time used by Harman Wold and Joreskog [34]  Cronbach’s alpha as well as composite reliability in PLS- SEM technique was used to check the reliability of constructs in region of Pakistan  The appropriate factor loading value for valid constructs should be greater than 0.700  Cross-factor loading value in PLS-SEM technique was used to check the discriminant validity.

  1. RESULTS AND DISCUSSION

The table below shows the reliability being greater than 0.6 hence showing that the questionnaire is reliable and could be used to study the prescribed variables. In this type of analysis, firstly measurement model is tested through testing the convergent and discriminant validity.

Table 01: Loading and Reliability Analysis

 

Variables

 

Items

 

Outer Loading

 

Cronbach’s Alpha

 

Composite Reliability

Average Variance Extracted (AVE)
Consumer Continues Intention INT1 0.926  

0.868

 

0.919

 

0.791

INT2 0.903
INT3 0.837
 

Satisfaction

SAT1 0.958  

0.917

 

0.948

 

0.858

SAT2 0.916
SAT3 0.905
Service Quality SER1 0.823  

0.847

 

0.908

 

0.767

SER2 0.911
SER3 0.891
 

System Quality

SYS1 0.843  

 

0.925

 

 

0.944

 

 

0.77

SYS2 0.898
SYS3 0.888
SYS4 0.862
SYS5 0.895
 

Trust

TRU1 0.886  

0.839

 

0.903

 

0.756

TRU2 0.881
TRU3 0.840

4.1 Outer loading

Table no. 1 shows the outer loadings of the indicators. According to the threshold value i-e >0.6, all the values show significant results. This sown the validity of the questionnaire.

4.2 Average Variance Extracted

Table no. 1 shows the AVE values for indicators. As this is an average value hence the threshold value tells that it has to be greater than 0.5. As all the values show significant results hence is the convergent validity.

Table 02: Fornell-Larcker Method

  Consumer Continues Intention  

Satisfaction

Service Quality System Quality  

Trust

Consumer Continues Intention  

0.889

Satisfaction 0.915 0.926
Service Quality 0.835 0.841 0.876
System Quality 0.680 0.764 0.791 0.877
Trust 0.882 0.868 0.817 0.760 0.869

Table no. 2 shows the values of average value extracted, which according to the threshold, has to be greater than 0.6. Here, the positive value shows the positive relationships, and the negative shows weaker or sometimes no result. The diagonal shows the maximum results. The above table has shown the positive and direct relation of variables with other variables and themselves. It, however, shows the highest positive relationship with themselves.

Table 03: Cross Loading

  Consumer Continues Intention  

Satisfaction

Service Quality System Quality  

Trust

INT1 0.926 0.880 0.763 0.640 0.882
INT2 0.903 0.821 0.748 0.681 0.788
INT3 0.837 0.728 0.718 0.478 0.662
SAT1 0.857 0.958 0.790 0.682 0.821
SAT2 0.835 0.916 0.765 0.667 0.777
SAT3 0.851 0.905 0.780 0.772 0.813
SER1 0.717 0.677 0.823 0.774 0.703
SER2 0.751 0.775 0.911 0.647 0.738
SER3 0.723 0.754 0.891 0.658 0.702
SYS1 0.569 0.622 0.630 0.843 0.672
SYS2 0.630 0.718 0.704 0.898 0.697
SYS3 0.572 0.670 0.666 0.888 0.642
SYS4 0.571 0.639 0.747 0.862 0.629
SYS5 0.639 0.698 0.722 0.895 0.689
TRU1 0.745 0.750 0.723 0.647 0.886
TRU2 0.716 0.660 0.642 0.628 0.881
TRU3 0.827 0.834 0.752 0.697 0.840

Table no. 3 has shown the results of cross-loadings which represent the loading of one construct with its own indicators and indicators of another. It tells that the value of the construct with itself should be maximum and should be lesser than that with others. According to this logic, satisfaction with satisfaction, service quality with service quality, system quality with system quality, and trust with trust show the highest loadings as compared to others  Although, the loadings show values higher than 0.4, which tells that kept result is validly Measuring the Structural model using PLS-SEM. The figure shown below contains the model run of PLS-SEM.

Figure 02: Structural Model PLS-SEM

In the above table, the causal relationships among different models are shown. In the inner model, the relationship between different proposed models is shown. Here, one unit increase in system quality will increase 0.219 units in the trust, one unit increase in service quality will increase 0.156 units increase in the trust, one unit increase in satisfaction will increase 0.565 units in the trust, and one unit increase in the trust will increase 0.882 units increase in continuous consumer intention.

Table 04: PLS-SEM Path Analysis

 

Sr.

No.

 

Hypothesis

 

Path Coefficients

 

T Statistics (|O/STDEV|)

 

P Values

 

Supported

 

H1

System Quality has a direct relation with trust  

0.158

 

7.594

 

0.000

 

Yes

H2 Service quality has a direct relation with trust 0.219 2.593 0.010 Yes
H3 Satisfaction has a direct relation with trust 0.565 2.019 0.044 Yes
 

H4

Trust has a direct relation with continuous consumer intention.  

0.882

 

43.583

 

0.000

 

Yes

4.3 T-Statistics

According to Joseph F. [34], the value of T- statistics for all the variables have to be greater than 1.96, and according to that, all the values give significant results. Hence it shows the goodness of fit of the model. The value for satisfaction -> Trust is 7.594; for Service Quality -> Trust, it’s 2.593; for System Quality -> Trust, it’s 2.019; for Trust -> Consumer Continues Intention, it’s 43.583, which according to threshold values, shows the maximum output.

4.4 P-value

The P-value tells that if the hypothesis we were to test turns out to be true or false. According to the results, all the hypothesis has been accepted as the threshold tells if the value of P for any combination is lesser than 0.05, we accept that very hypothesis [35]. Now the value of P Satisfaction -> Trust is 0.000, for Service Quality -> Trust is 0.010, System Quality -> Trust is 0.044, and for Trust -> Consumer Continues Intention 0.000. As all of them are lesser than 0.05, we accept all hypotheses. The results of PLS-SEM show a P-value of 0.000, which tells the significant positive relationship between system quality to trust, and 0.000, which shows the acceptance of the hypothesis. H1: Accepted H10: Rejected. Now, the system quality and trust show significant results, i-e 0.00, and has shown a significant direct result as well which is too 0.010. This proves the acceptance of another hypothesis. H2: Accepted H20: Rejected. Satisfaction with trust shows a P-value of 0.044 which again proves the acceptance of H3. H3: Accepted H30: Rejected. Lastly, trust, when measured with continuous consumer intention, shows a significant value of 0.000. This resultantly lets the acceptance of H4. The above statement shows that all the hypothesis were accepted, which means that if the system quality, service quality, and satisfaction gets better, the customer would intend to purchase the mobiles. Also, the service quality, system quality, and satisfaction combine to build trust that will then intended to create continuous consumer intention.

  1. CONCLUSIONS

After conducting a thorough review of the relevant literature, the researchers found that their predecessors had only infrequently investigated the continuous intention towards mobile purchase, particularly in Ghana  As a result, it is very important in terms of retaining a very decisive mobile vendor and making things easier for them  The goal of this study was to investigate the element that plays the most significant role in determining a customer’s propensity to make repeat purchases of mobile devices  We developed a model to test the effect of satisfaction, service quality, and system quality upon the continuous intention of consumers towards the purchase of mobile devices, taking into consideration the importance of trust  The findings suggested that trust is a component of service quality, system quality, and customer satisfaction; once established, trust is the driving force behind a consumer’s ongoing intention to make mobile purchases  According to the findings, the vendor needs to take into account the system and service quality of mobile devices, while the level of satisfaction enables a continuous intention to make a subsequent purchase  Despite the fact that this study was meticulously overseen and the results were interpreted with caution, every research endeavour has certain constraints  This research was carried out solely in Ghana, a country in which mobile commerce is expanding rapidly but is still in its infancy. We have high hopes that our research will serve as a benchmark in a variety of settings and that its findings will be put to use as a secondary source by a variety of national and international mobile companies in the course of their actual sales and additional research  We only surveyed the service and system quality, but there are many other factors that can be studied as well, such as the quality of the information, concerns about privacy and security, and individual user characteristics  The retention of customers will be greatly aided by this on the part of the vendors  Our research is based on a model that is cross-sectional, which precludes any possibility of checking its longitudinal analysis  If this study was carried out without any demographic restrictions, then it’s possible that our research will give different and more comprehensive results

REFERENCES

  1. Chopdar, P. K., Korfiatis, N., Sivakumar, V. J., & Lytras, M. D. (2018). Mobile shopping apps adoption and perceived risks: A cross-country perspective utilizing the Unified Theory of Acceptance and Use of Technology Computers in Human Behavior, 86, 109-128.
  2. Yang, K. (2010) Determinants of US consumer mobile shopping services adoption: implications for designing mobile shopping services  Journal of consumer marketing, 27(3), 262-270.
  3. Shaw, N., & Sergueeva, K. (2019) The non-monetary benefits of mobile commerce: Extending UTAUT2 with perceived value  International Journal of information management, 45, 44-55.
  4. Yang, K., & Forney, J. C. (2013) The moderating role of consumer technology anxiety in mobile shopping adoption: Differential effects of facilitating conditions and social influences  Journal of Electronic Commerce Research, 14(4), 334.
  5. Saprikis, V., Markos, A., Zarmpou, T., & Vlachopoulou, M. (2018) Mobile shopping consumers’ behavior: An exploratory study and review  Journal of theoretical and applied electronic commerce research, 13(1), 71-90.
  6. Li, M., Dong, Z. Y., & Chen, X. (2012). Factors influencing consumption experience of mobile commerce: A study from experiential view Internet Research, 22(2), 120-141.
  7. Faqih, K. M., & Jaradat, M. I. R. M. (2015). Assessing the moderating effect of gender differences and individualism-collectivism at individual-level on the adoption of mobile commerce technology: TAM3 perspective Journal of Retailing and Consumer Services, 22, 37-52.
  8. Gao, L., Waechter, K. A., & Bai, X. (2015). Understanding consumers’ continuance intention towards mobile purchase: A theoretical framework and empirical study–A case of China Computers in Human Behavior, 53, 249-262.
  9. Chong, A. Y. L., Chan, F. T., & Ooi, K. B. (2012). Predicting consumer decisions to adopt mobile commerce: Cross country empirical examination between China and Malaysia Decision support systems, 53(1), 34-43.
  10. Lu, J. (2014) Are personal innovativeness and social influence critical to continue with mobile commerce? Internet research, 24(2), 134-159.
  11. Zhang, L., Zhu, J., & Liu, Q. (2012) A meta-analysis of mobile commerce adoption and the moderating effect of culture Computers in human behavior, 28(5), 1902-1911.
  12. Jaradat, M. I. R. M., & Al Rababaa, M. S. (2013). Assessing key factors that influence the acceptance of mobile commerce based on modified UTAUT International Journal of Business and Management, 8(23), 102.
  13. Liébana-Cabanillas, F., Marinković, V., & Kalinić, Z. (2017). An SEM-neural network approach for predicting antecedents of m-commerce acceptance International Journal of Information Management, 37(2), 14-24.
  14. Yang, K. (2012) Consumer technology traits in determining mobile shopping adoption: An application of the extended theory of planned behavior Journal of Retailing and Consumer Services, 19(5), 484-491.
  15. Blaise, R., Halloran, M., & Muchnick, M. (2018). Mobile commerce competitive advantage: A quantitative study of variables that predict m-commerce purchase intentions Journal of Internet Commerce, 17(2), 96-114.
  16. Agrebi, S., & Jallais, J. (2015). Explain the intention to use smartphones for mobile shopping Journal of Retailing and consumer services, 22, 16-23.
  17. Zarmpou, T., Saprikis, V., Markos, A., & Vlachopoulou, M. (2012) Modeling users’ acceptance of mobile services Electronic Commerce Research, 12, 225-248.
  18. Ozturk, A. B., Bilgihan, A., Nusair, K., & Okumus, F. (2016). What keeps mobile hotel booking users loyal? Investigating the roles of self-efficacy, compatibility, perceived ease of use, and perceived convenience International Journal of Information Management, 36(6), 1350-1359.
  19. Alalwan, A. A., Baabdullah, A. M., Rana, N. P., Tamilmani, K., & Dwivedi, Y. K. (2018) Examining adoption of mobile internet in Saudi Arabia: Extending TAM with perceived enjoyment, innovativeness, and trust Technology in Society, 55, 100-110.
  20. Claudy, M. C., Garcia, R., & O’Driscoll, A. (2015) Consumer resistance to innovation—a behavioral reasoning perspective Journal of the Academy of Marketing Science, 43, 528-544.
  21. Wang, W. T., & Li, H. M. (2012). Factors influencing mobile services adoption: a brand‐equity perspective Internet research.
  22. Wu, L., Li, J. Y., & Fu, C. Y. (2011). The adoption of mobile healthcare by hospital professionals: An integrative perspective Decision support systems, 51(3), 587-596.
  23. Lin, H. F. (2011) An empirical investigation of mobile banking adoption: The effect of innovation attributes and knowledge-based trust International Journal of information management, 31(3), 252-260.
  24. Zhao, Y., Ni, Q., & Zhou, R. (2018) What factors influence the mobile health service adoption A meta-analysis and the moderating role of age  International Journal of Information Management, 43, 342-350.
  25. Shaikh, A. A., & Karjaluoto, H. (2015). Mobile banking adoption: A literature review Telematics and informatics, 32(1), 129-142.
  26. Yeo, V. C. S., Goh, S. K., & Rezaei, S. (2017) Consumer experiences, attitude and behavioral intention toward online food delivery (OFD) services Journal of Retailing and Consumer Services, 35, 150-162.
  27. Li, Y. M., & Yeh, Y. S. (2010) Increasing trust in mobile commerce through design aesthetics Computers in Human Behavior, 26(4), 673-684.
  28. Kim, Y. H., Kim, D. J., & Wachter, K. (2013). A study of mobile user engagement (MoEN): Engagement motivations, perceived value, satisfaction, and continued engagement intention Decision support systems, 56, 361-370.
  29. Oliveira, T., Thomas, M., Baptista, G., & Campos, F. (2016). Mobile payment: Understanding the determinants of customer adoption and intention to recommend the technology Computers in human behavior, 61, 404-414.
  30. Heitz-Spahn, S. (2013). Cross-channel free-riding consumer behavior in a multichannel environment: An investigation of shopping motives, sociodemographics and product categories Journal of Retailing and consumer services, 20(6), 570-578.
  31. Slade, E. L., Dwivedi, Y. K., Piercy, N. C., & Williams, M. D. (2015) Modeling consumers’ adoption intentions of remote mobile payments in the United Kingdom: extending UTAUT with innovativeness, risk, and trust Psychology & Marketing, 32(8), 860-873.
  32. Persaud, A., & Azhar, I. (2012). Innovative mobile marketing via smartphones: Are consumers ready? Marketing Intelligence & Planning, 30(4), 418-443.
  33. Attasuda & Thitima (2022). Impacts of economic conditions on mental health: a case study of Thailand Dinkum Journal of Economics and Managerial Innovations, 1(01):30-39.
  34. De Luna, I. R., Liébana-Cabanillas, F., Sánchez-Fernández, J., & Muñoz-Leiva, F. (2019). Mobile payment is not all the same: The adoption of mobile payment systems depending on the technology applied Technological Forecasting and Social Change, 146, 931-944.
  35. Koenig-Lewis, N., Marquet, M., Palmer, A., & Zhao, A. L. (2015). Enjoyment and social influence: predicting mobile payment adoption. The Service Industries Journal, 35(10), 537-554.

Publication History

Published: March 01, 2023

Identification

D-0039

Citation

Baah Lydia, Nyantakyi Tetteh, and Masud Kong, (2023). Consumers’ behavioral motives towards adoption of mobile commence in Ghana. Dinkum Journal of Economics and Managerial Innovations, 2(03):163-173.

Copyright

© 2023 DJEMI. All rights reserved