Motives towards e-Shopping Adoption among Pakistani Consumers: An Application of the Technology Acceptance Model and Theory of Reasoned Action

Round 1

Reviewer 1 Report

I recommendent to publish! Good day!

Author Response

Point 1: I recommended to publish! Good day!

Response: Thank you very much for accepting our research work.

Author Response File: Author Response.docx

Reviewer 2 Report

Thank you for the opportunity to read this study.

The paper is grounded but does not bring any innovative ideas.

 The authors affirm that "Online buying patterns, in contrast, are based on only two stages—the first stage involves finding, comparing, and selecting products or services, including the placing of orders, and the second stage consists of order tracking, delivery, and the returning of anything that does not meet consumer expectations. "

But " facing problems with delivery time, quality issues, and defective products despite how rapidly technology has accelerated in terms of online retail" is not related to (V) -post purchase behavior?

And " some have become reputable among customers by gaining high customer satisfaction and trust, including Daraz, Telemart, IShopping, HomeShopping, Goto, Yaoyvo, Shophive, and online cloths brand stores 
such as Khaadi, Limelight, Gulahmad, Sapphire and Sanasafinaz, " are not related to (i) need recognition?

The authors have to emphasize the link  between EKB and TAM, TRA
H1a, H2a, H3a - might form one hypothesis. The same H1b-H3b, H1c-H3c, H1d_H3d.
How can you measure it? Which is the question in the survey?

Usually, when Loading Factors, Cronbach, and CR are so high the multicollinearity is presented, affecting the model. The author has to check this issue and offer supplementary information.

The Discussion section is missing and the Conclusions are too laconic.

 The authors should read and cite articles published in Scopus, WoS, etc in the last 3 years.

Author Response

Point 1: The paper is grounded but does not bring any innovative ideas.

Response: Thank you for comment, the paper is based on understanding the consumer behavior towards e-shopping of under-developing country like Pakistan. In today globalization, Pakistan is also trying to uplift the digital economy and e-commerce specifically online shopping play a vital role toward this move. According to e-shopping literature about Pakistan only few studies has been conducted to understand the consumer behavior in different prospective, but this paper provides different factors which are related to technology acceptance and Table 1 is expressed the gap or need of study. However, from page 2 to page 3 included research questions expressed the need of this study in more detail. (Highlighted in yellow).

Point 2: The authors affirm that "Online buying patterns, in contrast, are based on only two stages—the first stage involves finding, comparing, and selecting products or services, including the placing of orders, and the second stage consists of order tracking, delivery, and the returning of anything that does not meet consumer expectations. " But " facing problems with delivery time, quality issues, and defective products despite how rapidly technology has accelerated in terms of online retail" is not related to (V) -post-purchase behavior? And " some have become reputable among customers by gaining high customer satisfaction and trust, including Daraz, Telemart, IShopping, HomeShopping, Goto, Yaoyvo, Shophive, and online cloths brand stores such as Khaadi, Limelight, Gulahmad, Sapphire, and Sanasafinaz, " are not related to (i) need recognition?

Response: Thanks for highlighting the effective point; the authors have modified the manuscript as per reviewer guidelines from page 2 line 7 to 21.

“.. With technology, traditional shopping styles (also known as in-person mall visits) are less convenient than the online shopping [15]. In a seminal work of existing literature, the Engel Kollat Blackwell (EKB) model is proposed to analyze consumer behavior in the context of traditional shopping styles [16]. The EKB model is established in five stages including (i) need recognition, (ii) information search, (iii) evaluation of alternatives, (iv) purchase decision, and (v) post-purchase behavior [17,18]. The EKB model is also a comprehensive tool that can help to understand the consumer buying decision process under technological development. In the online purchasing decision model, the EKB model stages have been merged into a two-stages—the first stage involves finding, comparing, and selecting products or services, including the placing of orders stage one is the combination of four stages of the EKB model such as (i) need recognition, (ii) information search, (iii) evaluation of alternatives, (iv) purchase decision and the second stage consists of order tracking, delivery, and the returning of anything that does not meet consumer expectations which is related to EKB model fifth stage i.e. post-purchase behavior [19,20]..”

Reference:

Jain, N.K.; Kaul, D.; Sanyal, P. What drives customers towards mobile shopping? An integrative technology continuance theory perspective. Asia Pacific J. Mark. Logist. 2021, 2014, doi:10.1108/APJML-02-2021-0133.

Osei, B.A.; Abenyin, A.N. Applying the Engell–Kollat–Blackwell model in understanding international tourists’ use of social media for travel decision to Ghana. Inf. Technol. Tour. 2016, 16, 265–284, doi:10.1007/s40558-016-0055-2.

Joseph C. Bonnice AN APPLICATION OF THE ENGEL , KOLLAT AND BLACKWELL MODEL TO CONSUMERS OF AUTOMOBILE INSURANCE Author ( s ): Joseph C . Bonnice Source : The Journal of Insurance Issues and Practices , January 1985 , Vol . 8 , No . 1 Published by : Western Risk and Insuran. J. Insur. Issues Pract. 1985, 8, 23–41.

Li, H.; Zhao, N. Better earlier than longer: First-Mover Advantage in social commerce product information competition. Sustain. 2019, 11, doi:10.3390/su11174630.

Han, Y.; Zhang, T.; Wang, M. Holiday travel behavior analysis and empirical study with Integrated Travel Reservation Information usage. Transp. Res. Part A Policy Pract. 2020, 134, 130–151, doi:10.1016/j.tra.2020.02.005.

Petcharat, T.; Leelasantitham, A. A retentive consumer behavior assessment model of the online purchase decision-making process. Heliyon 2021, 7, e08169, doi:https://doi.org/10.1016/j.heliyon.2021.e08169.

Xue, L.L.; Shen, C.C.; Morrison, A.M.; Kuo, L.W. Online tourist behavior of the net generation: An empirical analysis in taiwan based on the aisas model. Sustain. 2021, 13, 1–18, doi:10.3390/su13052781.

Chawla, M.; Khan, M.; Pandey, A. ONLINE BUYING BEHAVIOUR: ABrief REVIEW AND UPDATE. J. Manag. Res. 2015, 9.

Lin, C.; Lekhawipat, W. Factors affecting online repurchase intention. Ind. Manag. Data Syst. 2014, 114, 597–611, doi:10.1108/IMDS-10-2013-0432.

Meixian, L. Convenience and online consumer shopping behavior: A business anthropological case study based on the contingent valuation method. Anthropologist 2015, 21, 8–17, doi:10.1080/09720073.2015.11891788.

Jiang, L. (Alice); Yang, Z.; Jun, M. Measuring consumer perceptions of online shopping convenience. J. Serv. Manag. 2013, 24, 191–214, doi:10.1108/09564231311323962.

Point 3: The authors have to emphasize the link between EKB and TAM, TRA.

Response: The main objective of the paper is to develop the link among the Online purchase model, TAM and TRA which was extensively expressed in the literature review. However, as per reviewer’s suggestion, we develop the relevancy of the EKB model with Online purchase model and then expressed the TAM and TRA from page 2 lines 12 to 21, and lines 28 to 32.  

“..The EKB model is also a comprehensive tool that can help to understand the consumer buying decision process under technological development. In the online purchasing decision model, the EKB model stages have been merged into a two-stages—the first stage involves finding, comparing, and selecting products or services, including the placing of orders stage one is the combination of four stages of the EKB model such as (i) need recognition, (ii) information search, (iii) evaluation of alternatives, (iv) purchase decision and the second stage consists of order tracking, delivery, and the returning of anything that does not meet consumer expectations which is related to EKB model fifth stage i.e. post-purchase behavior [19,20]..”

“…Eventually, the benefits of online purchasing such as convenience, better price comparison, more product variety, privacy, and time-saving are highly effective to reshape the consumer behavior and technology acceptance model (TAM) and the theory of reasoned action (TRA) is the most influential theories to explain and predict users’ acceptance of the new system [25]..”

References:

Han, Y.; Zhang, T.; Wang, M. Holiday travel behavior analysis and empirical study with Integrated Travel Reservation Information usage. Transp. Res. Part A Policy Pract. 2020, 134, 130–151, doi:10.1016/j.tra.2020.02.005.

Petcharat, T.; Leelasantitham, A. A retentive consumer behavior assessment model of the online purchase decision-making process. Heliyon 2021, 7, e08169, doi:https://doi.org/10.1016/j.heliyon.2021.e08169.

Patsiotis, A.; Atik, M.; Perrea, T. The influence of m-marketing tools on consumer buying process: evidence from the dining sector. Int. J. Retail Distrib. Manag. 2020, 48, 1037–1056, doi:10.1108/IJRDM-06-2018-0109.

Point 4: H1a, H2a, H3a - might form one hypothesis. The same H1b-H3b, H1c-H3c, H1d_H3d.

Response: Thank you for the suggestion, Eventually, this study focuses on four factors of online purchasing behavior and describes them as independent variables—personal awareness of security, perceived usefulness, personal innovativeness, and perceived ease of use. We assess the direct impact of these factors on consumers’ intentions for online purchasing (the dependent variable) as well as the mediating effects via consumers’ attitudes toward online purchasing (a mediating variable). Fig. 1 demonstrates the proposed research model of the study. This study follows the Barron & Kenney (1986) method to test the mediation hypotheses [1]

H1 hypotheses series (H1a, H1b, H1c, H1d) based on IVs vs DV

H2 hypotheses series (H2a, H2b, H2c, H2d) based on IVs vs mediator

H3 hypotheses series (H3a, H3b, H3c, H3d) based on IV vs DV with the presence of a mediator

H4 is based on mediator vs DV

Reference:

Baron, R.M.; Kenny, D.A. The moderator--mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. J. Pers. Soc. Psychol. 1986, 51, 1173.

Point 5: How can you measure it? Which is the question in the survey?

Response: Thank you for highlighted point related to the survey. Subsection 3.2 expressed the measurement detail and we have also added the Survey questions in Appendix 1.

Point 6: Usually, when Loading Factors, Cronbach, and CR are so high the multicollinearity is presented, affecting the model. The author has to check this issue and offer supplementary information.

 Response: We have added the multicollinearity result in the manuscript from page 10 line 16 to 17 and page 11 line 1 to 6.

“….Regression analysis ware examined to analyze the results of the proposed hypothesis. Before examining the regression analysis multicollinearity analysis has been performed using variance inflation factor (VIF) test and tolerance level method. According to literature, the VIF value must be smaller than 10, and the tolerance level value is greater than 0.1, these values are considered threshold values [67,68]. The results of VIF and tolerance level of this study is under acceptable value such as no VIF found more than 10 and tolerance level is also less than 0.10, therefore, we conclude that this study has no issue of multicollinearity. The detailed results of regression analysis are presented in the following subsection..”

 

References:

Iasemidis, L.D.; Schachter, S.; Fregni, F.; Ilmoniemi, R. Regression Methods in Biostatistics; 2013; Vol. 23; ISBN 9781461413523.

Bakar, A.A.; Afthanorhan, A. Confirmatory Factor Analysis on Family Communication Patterns Measurement. Procedia - Soc. Behav. Sci. 2016, 219, 33–40, doi:https://doi.org/10.1016/j.sbspro.2016.04.029.

Point 7: The Discussion section is missing, and the Conclusions are too laconic.

Response: Section 4 is based on results and discussion. The authors expressed the discussion according to the result of the proposed hypotheses (highlighted in yellow).

Point 8: The authors should read and cite articles published in Scopus, WoS, etc in the last 3 years.

Response: TAM and TRA theories are presented 80’s, therefore, while explaining these theories old citation was presented. However, we have modified the references according to the reviewer suggestions as well academic editors’ guidelines.

Author Response File: Author Response.docx

Reviewer 3 Report

Thanks for sharing this manuscript with me. I only have one suggestion and I hope that the manuscript can be thus improved.

It is necessary to clarify the importance and uniqueness of this manuscript as well as the findings. For example, what would differentiate this manuscript from the existing publications? Does this manuscript show up anything that scholars and managers did not know or understand from the extant literature? After all, so many papers have been published with the similar findings regarding e-shopping behaviors, intentions, and so forth.

Author Response

Point 1: Thanks for sharing this manuscript with me. I only have one suggestion and I hope that the manuscript can be thus improved. It is necessary to clarify the importance and uniqueness of this manuscript as well as the findings. For example, what would differentiate this manuscript from the existing publications? Does this manuscript show up anything that scholars and managers did not know or understand from the extant literature? After all, so many papers have been published with the similar findings regarding e-shopping behaviors, intentions, and so forth.

Response: Thank you very much for your comment. The paper is based on understanding the consumer behavior towards e-shopping of the under-developing country like Pakistan. In today’s globalization, Pakistan is also trying to uplift the digital economy and e-commerce more specifically online shopping plays a vital role in this move. According to e-shopping literature about Pakistan, only a few studies have been conducted to understand consumer behavior from a different perspective, but this paper provides different factors which are related to technology acceptance and Table 1 (highlighted in green) is expressed the gap or need of study. However, page 2 (last paragraph) and page 3 included research questions that expressed the need for this study in more detail. Moreover, In the context of Pakistan, previous research has not described these determinants in evaluating consumer behaviors using these theories. We conclude that the highlighted factors are very crucial for consumer adoption of technological advancements following the technology acceptance model. For practical and theoretical contributions, our findings have important implications for theory. First, this study expands our understanding of online purchasing intention by using the technology acceptance model and theory of reasoned action. Secondly, the current research supports contributes, and broadens the existing literature by considering four major factors—personal awareness of security, perceived usefulness, personal innovativeness, and perceived ease of use (purchasing)—in online consumer behaviors in Pakistan. From a practical point of view, this study guides managers to understand consumer behaviors in online purchasing using proposed factors.

All these points are included manuscript.

Author Response File: Author Response.docx

Reviewer 4 Report

Data were collected from an online survey and evaluated using SPSS and AMOS statistical software. Results revealed that the identified factors are positively and significantly related to consumer intentions and attitudes toward online purchasing. 

Author Response

Point 1: Data were collected from an online survey and evaluated using SPSS and AMOS statistical software. Results revealed that the identified factors are positively and significantly related to consumer intentions and attitudes toward online purchasing. 

Response: I think the reviewer suggests that SPSS and AMOS are not mentioned in the Abstract. We deleted these lines from the abstract and modified the abstract.

Author Response File: Author Response.docx

Round 2

Reviewer 2 Report

Thank you for the improvements.

I haven't seen a table with VIF values

I prefer this interpretation for VIF: 

https://methods.sagepub.com/base/download/DatasetStudentGuide/sem-customer-behavior-electronics-ecuador 

https://www.statisticshowto.com/variance-inflation-factor/ 

http://onlinehelp.ihs.com/Energy/AnalyticsExplorer/AE_7.0/Webhelp/content/analyticsexplorer/VIF.htm

Please make this update 

Author Response

Thank you very much for reviewing the manuscript. We have added VIF values in Table 6. 

Reviewer 3 Report

No further comment.

Author Response

Thank you very much for accepting our research work.