The Effect of Digital Marketing Adoption on SMEs Sustainable Growth: Empirical Evidence from Ghana

Round 1

Reviewer 1 Report

GENERAL COMMENTS

The authors deal with a very interesting and significant topic. The manner in which they structure their manuscript can be assessed as very successful. The quantity of sources they rely on also deserves support. Nevertheless, there are issues that need to be resolved before considering the acceptance of the manuscript. I will elaborate on them in several sections. Additionally, the examples I provide should be considered as an invitation to find all analogous places within the manuscript and not as a finished list of issues authors should deal with.

I GREATER CAUTION WITH RELYING ON THE CITED LITERATURE

1.1. When citing research about different TPB variables

- The authors rely on a wide range of literature (from sources implementing only TPB or only TAM, to manuscripts relying on the decomposed TPB, adding different new variables to it, and even omitting some of the original variables). Therefore, the authors should briefly present that context. The lack of such caution can lead to serious mistakes such as those regarding hypothesis 5, which will be described below.   

1.2. The problem with hypothesis 5

- In the original TPB, in addition to the behavioral intention influencing actual behavior, actual behavior is determined by PBC (PBC together with attitudes and SN influence behavioral intention). In this model, however, such a relation is not considered but is considered the moderating effect of SN on the relationship between behavioral intention and actual behavior.

- When formulating this hypothesis authors rely on several sources:

·        [86] according to which authors stress that “subjective norms can moderate between intention to use and actual usage in the context of tourism”. The problem is that there is no actual usage in the cited research, nor there are moderating effects of SN. Actually, the effect of SN on behavioral intention is moderated by two other variables.

·        [109] – in this research SN is not a moderator as the authors describe in this hypothesis. There is no effect of it when it comes to the relation between behavioral intention and actual behavior.

·        [110] – in this research SN is the moderator, but independent variables are different types of risks that directly influence behavior. (When you see such a model, the significance to describe the context (according to my objection in 1.1.) becomes even more apparent).

·        [111] – relies on the TAM model but the independent variables (which in the original TAM model influence the attitude, which influences behavioral intention, which finally influences actual behavior) in this research influence directly actual behavior. Here should be stressed that when choosing the sources to cite, authors should not consider as sufficient that the manuscript was published in a journal but should also have a critical stance towards it.

- Having all this in mind, I believe there is no justification for formulating hypothesis 5.

1.3. There is no need to call upon too many sources when not needed. For example, when describing methodology, it is sufficient to rely on Hair et al. (2019). There is no need to cite some other research using a similar methodology because such a list can be almost endless.

1.4. In the research cited by the authors, as well as in all the literature regarding the topic (at least known to me), it is not recommended for Cronbach’s alpha to be above 0.5 – the recommended thresholds are different.

 

II THE PROBLEM OF MEASURING THE VARIABLES

Similar problems as described above appear when it comes to measuring the Actual use of DM, and SMEs’ sustainable growth. I would even dare to suggest that the items used for measuring these two variables can not measure them, at least as formulated in the model.

If we rely on the sources authors use for measuring sustainable growth, we could notice the following:

-        There are no similar items in [2] for measuring the variable.

-        Sources [48] and [135] do not measure that variable at all.

-        The only relatively similar research when it comes to the measurement of sustainable growth to this research is [151]. Although some items used in it resemble items authors use in this research, there are important differences. Let’s look at one of the items from [151]: “I believe that our organization performance has been improved after using social media platform.” Such an item is related to the results of the concrete organization and in connection to performing the concrete change. In this research, authors rely on, for example: “Digital marketing usage can improve their sales growth through frequent interaction with the customers.” Such a formulation is general and might measure the attitude of the respondents regarding digital marketing contribution to sustainable growth but not the actual sustainable growth of an organization as a result of DM.

We can notice similar findings for the variable Actual use of DM:

-        In [86] there is no variable related to actual behavior.

-        In [103], actual behavior is measured from the buyer’s perspective and two implemented items “I would buy a car based on the information available over digital media” and “I would like to book a car online for purchasing” do not resemble in any manner to items authors use in this research.

-        Partial comparability can again be found only with [151]. But again, in that research, there are items like “We have social media enabled customer relationship management tools which we regularly use” that do measure actual use. Unfortunately, such items do not exist in this research.

The authors might suggest that cited manuscripts were their “inspiration” for the formulation of items. Nevertheless, if they are developing their own scales, there is a scientific procedure for it that is not presented in this paper. In addition, it does not eliminate the greatest problem – the items used for measuring these two variables can not measure them, at least as formulated in the model.

To conclude, the authors need to justify that the items they rely on actually measure two mentioned variables. If it is not possible (I am deeply skeptical about such a possibility), they could choose among two possible solutions. The first is to reformulate those two variables and conduct research once again. The second is to use the TPB model without those two variables (numerous authors actually use behavioral intention as the last dependent variable within the TPB model). In that case, there should be adaptations starting from the title of the paper to all other relevant elements.

 

III SAMPLING DILEMMAS

It is not described how a simple random sample was obtained. At first, the authors describe SMEs using digital marketing in Ghana as a population from which the sample was drawn. Nevertheless, they also suggest that only those SMEs “who have largely used digital marketing to fuel their sustainable growth were subjected to the inquiry”. It implies a narrower population. We do not know what is the threshold for “large use of DM to fuel own sustainable growth”. What was the sampling frame? From which lists were SMEs chosen? In which manner?

 

IV NO MODERATION ANALYSIS

The authors did not actually perform any moderation analysis. They observed the influence of SN on the intention to use DM and on the actual use of DM. However, the path coefficient from the last case does not prove moderation (it actually proves the direct effect of SN on the actual use of DM). There should be a new variable derived as an interaction of SN and intention to use DM. A significant influence of that variable (interaction effect) would prove moderation. For more details on moderation analysis, the authors could rely on, for example:  

Becker J-M, Ringle CM and Sarstedt M. (2018) Estimating Moderating Effects in PLS-SEM and PLSc-SEM: Interaction Term Generation*Data Treatment. Journal of Applied Structural Equation Modeling 2(2): 1-21.

 

V THE NEED FOR DEEPER INTERPRETATION OF THE OBTAINED RESULTS

We can start by quoting the authors:

“First, the study hypothesized that attitude toward digital marketing would positively influence the intention to use digital marketing. This finding is inconsistent with [48, 51, 61, 62], who observed a significant relationship between attitude toward digital marketing and intention to use to digital marketing.”

First, the problem is in the language. We can read about the assumption. We can also see the comment that the results are inconsistent with previous studies. But, we miss the results – we only see “this finding”. Second, the problem is the interpretation. After quoted sentences, there is only an explanation of the positive relationship between attitudes and behavioral intention in other studies. Nevertheless, we see no explanation why in this research the results are so unusual and no relationship between the two variables was found.

 VI TECHNICAL ISSUES

-        There is provided a definition by the authors without providing the page of the original manuscript from which it was quoted.

-        There are sentences starting with [] filled in with the appropriate number.

-        The manner in which Figure 1 is drawn (the arrow from Actual use of DM to SMEs’ sustainable growth).

-        Actual use of DM is not named in the model provided in Appendix (instead, it is marked as a Latent variable).

-        There is no interaction effect in the same model.

-        The authors might present descriptive statistics for all of the constructs.

Author Response

Thank you for your comments. We have uploaded the revision in the system. 

Author Response File: Author Response.pdf

Reviewer 2 Report

This is a paper with a solid work base. However, serious issues exited in this paper. I would like to make the following points to help the author improve the quality of the paper:

1. This version you presented to me seems not checked. Please see Figure 1, the H6 link seems not points to sustainable growth.

2. Please remake table 1 according to MDPI format, instead of retrieving from google form. What SSSCE in Table 1 stands for?

3. I am not sure VIF is a common way to verify CMV issue although VIF is usually used to test collinearity problem. CMV is not the same with collinearity problem. Please provide other evidences to rule out CMV (e.g., harman single factor; Common marker variable).

4. Provide CFA result (fitness indices; such as CFI, TLI, SRMR) and the contest model CFA results.

5. As a survey study, the correlations of variables in your study reached 0.839 (intention to use DM and latent variable 6). What is latent variable 6? All your correlations exceed 0.54, proving a serious CMV issue. Please explain it.

 

Author Response

Thanks for the comments, we have uploaded the responds in the system. Thank you

Author Response File: Author Response.pdf

Reviewer 3 Report

1. In the introduction, an explanation of what differentiates this study and why this study is necessary should be presented. A brief description of the main variables of this study and how this study model differs from previous studies should be given.

2. An explanation should also be given as to why the hypothesis was not established about the relationship between "Attitude towards digital marketing and Perceived behavioral control" and "Actual behavioral use of digital marketing". In addition, an explanation for why the hypothesis on the relationship between "actual behavioral use of digital marketing" and "SMEs sustainable growth" was not established should be presented.

3. As the sample of this study consists of five business areas, it is expected that the use of digital marketing in these businesses will make a difference in their continued business growth, and an explanation for this should also be provided.

4. When presenting the implications of this study, the theoretical implications and practical implications should be divided and richly presented based on the results of the empirical analysis.

Author Response

Thank you for the comments and suggestions. Please we have uploaded the response.

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

Unfortunately, the authors did not succeed in resolving the greatest problem as noticed in my previous comments. They were not able to justify that the items they rely on actually measure two variables - actual use of DM and SMEs sustainable growth. Some other changes they performed also do not suggest that they patiently and profoundly considered my comments. Again, we have no information from which list of SMEs were randomly chosen participants for this research. Therefore, I have to suggest rejecting the article.

Nevertheless, I again repeat two suggestions that might make it potentially acceptable for a new upload in the future. The first is to reformulate two variables (actual usage and sustainable growth) and conduct research once again. The second is to use the TPB model without those two variables (numerous authors actually use behavioral intention as the last dependent variable within the TPB model). In that case, there should be adaptations starting from the title of the paper to all other relevant elements. Of course, this should be followed by a precise literature review and sampling technique description.

 

Author Response

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Author Response File: Author Response.pdf

Reviewer 2 Report

See attached PDF

 

Comments for author File: Comments.pdf

Author Response

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Author Response File: Author Response.pdf

Round 3

Reviewer 1 Report

Unfortunately, I see no substantial improvements in the manuscript. That is why I continue to suggest that the manuscript should be rejected.

I will deal with two theses from my previous review once again.

I

The first is that the authors do not measure some of the variables appropriately. Let’s consider, for example, the variable Actual usage of DM. The authors rely on the following items:

1. Frequent usage of digital marketing helps to understand customers’ opinion about our products

2. Regularly use of digital marketing enabled customer relationship management

3. We believe frequent use of digital marketing for marketing purpose helps in improving competitiveness

I do not have doubts that digital marketing is useful for understanding customers, CRM, and competitiveness. But those items do not measure its actual usage.

In order to understand how actual behavior (actual usage in this context) is measured I suggest to the authors to read Ajzen’s (2019): CONSTRUCTING A THEORY OF PLANNED BEHAVIOR QUESTIONNAIRE (available at: https://people.umass.edu/aizen/pdf/tpb.measurement.pdf)

II

The second problem is again with sampling. I feel once again that the authors do not pay enough attention to comments. The authors write: “The list of the SMEs selected were also provided as shown in Table 2 of the manuscript.“  It is actually Table 1. But, that is not what I asked for. I asked them to describe from which list they chose those 533 SMEs. And not the list of 533 SMEs.

I will explain deeper. The authors say they use simple random sampling. If they implement such an approach they would first need to have a list of all SMEs from Ghana (or at least of all SMEs from chosen sectors) (let’s imagine that list (if there is any) consists of 10,000 SMEs, whereas each SME has its own ID). Then they would need to select 650 random numbers (that is their starting sample size). Let’s say that the first two random numbers out of 650 numbers (ranging from 1 to 10,000) are 3 and 45 (the list would, of course, continue). The authors would have to contact SME with ID 3 and SME with ID 45 from that 10,000 SMEs list (and so on) to obtain a simple random sample.

If they did not follow a similar procedure, they actually do not implement a simple random sampling.

Author Response

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Author Response File: Author Response.pdf

Reviewer 2 Report

No further suggestions. PLESAE provide CFI, TLI, SRMR in your publised version. YOU didn't include these indexs in current version.

 

Author Response

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Author Response File: Author Response.pdf