Submitted:
14 August 2024
Posted:
14 August 2024
You are already at the latest version
Abstract
Keywords:
1. Introduction
- First step – to assess the degree of use of digital marketing tools by Polish SMEs against the EU average based on secondary data (reports of the European Commission, Eurostat, Statistics Poland),
- Second step - to evaluate the application of the digital communication and sale tools by Polish SMEs in the context of economic results based on primary data (survey results) and statistical methods.
2. Literature Review
2.1. Development of New Technology in Marketing and Customer Service
RS 1: Is the use of the digital communication and sale tools by Polish SMEs at the same level as in the EU?
2.2. Measurable Benefits of Modern Tool Implementation
RS 2: What impact have the use of traditional and digital marketing communication and sale tools of Polish SMEs on economic performance?
3. Materials and Methods
3.1. Theoretical Basis and Justification for the Choice of Research Methodology
- -
- Cronbach's alpha test- a test used to assess the reliability of surveys, and required for survey design,
- -
- Kolmogorov-Smirnov test- the test used to assess the normality distri-bution of the variables and required to determine the selection of further statistical tools,
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- Mann-Whitney U test- the test is suitable to test differences of 2 groups for ordi-nal dependent variable (Likert scale),
- -
- ANOVA Kruskal-Wallis tests and Dunn's post-hoc tests - test is suitable for the number of samples exceeding 2, for ordinal dependent variable (Likert scale),
- -
- Kendall's rank correlation coefficient- a coefficient used in socioeconomic research to examine the relationship between variables that are rated in a Likert scale survey,
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- MARSplines (Multivariate Adaptive Regression Splines)-a non-parametric statistical regression me-method used to establish model predictors.
3.2. Sample
3.3. Procedure
- H0 2 Companies use traditional and modern customer communication methods to the same extent
- H0 3 Companies use traditional and modern sale methods to the same extent
- H0 4 Obstacles on the part of the company and of the customers limit modern technology implementation to the same extent
- H0 5 Companies use traditional and modern customer service tools to the same extent
- H0 6 Using particular communication and sale methods and obstacles to their implementation do not influence the economic results of the company
- H0 7 The implementation of modern technologies in the area of sale and customer service affects the individual economic effects to the same extent
3.4. Research Tools
4. Results
4.1. Statistical Data Analysis
4.2. Summary of Survey Results
5. Discussion
6. Conclusions
- Polish SMEs make lower use of modern digital tools for communication and sales compared to companies in the EU,
- the studied companies use modern communication and sale tools to a low extent as they mostly employ traditional channels and methods;
- the obstacles to implementing modern communication and sale methods referring to the limitations on the company’s part decrease economic results. These are: the absence of sufficient funds, insufficient expertise and employees’ competence;
- the studied companies perceive the positive effect of the modern solutions on the financial results but see also that this entails future investment expenditure.
Theoretical Implications:
- deepening the concept of Schultz Integrated Marketing Communications - IMC [108],
- basis for international comparisons in the use of digital marketing tools by SMEs in different economies,
- basis for cross-industry comparisons.
Practical Implications
- organization of training and providing advice to micro-, small and medium-sized enterprise managers relating to the adaptation of human resources and innovation processes to the digital era challenges;
- development of intensive courses developing digital skills of SME employees relating to artificial intelligence, cybersecurity and blockchain;
- financial support for SMEs in their efforts to increase the advanced technology use, e.g. for buying license and software enabling to implement digital solutions;
- informing SMEs and encouraging them to create start-up ecosystems, increase the number of digital innovation hubs (DIH) in connection with the Startup Europe initiative and the European Network;
- activities oriented toward the development and improvement of the Enterprise Europe Network offering services adapted to SME’s needs.
Research Limitations and Directions for Further Research
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Appendix A
| Question no. |
Question |
|---|---|
| Q1 | In our company, we communicate with our customers using traditional methods (meeting in the company seat, phone, traditional mail, email etc.) |
| Q2 | In our company, we communicate with our customers using modern communication methods (Facebook, Twitter, Instagram, WhatsApp, Messenger, livechat, mobile application) |
| Q3 | Our company customers most often buy using traditional methods in the company seat |
| Q4 | Our company customers most often buy from our e-shop |
| Q5 | Our company customers most often buy from other e-shops offering our products |
| Q6 | Modern technology implementation in customer service area contributes to improved service speed and effectiveness |
| Q7 | Modern technology implementation in customer service area contributes to increased customer satisfaction |
| Q8 | Modern technology implementation in customer service area contributes to improved financial results |
| Q9 | Modern technology implementation in customer service area contributes to improved company image |
| Q10 | Major obstacles to implementing cutting-edge technology in the customer service area are the ones on the company’s part (e.g. absence of funds, low employee competences, absence of expertise). |
| Q11 | Major obstacles to implementing cutting-edge technology in the customer service area are the ones on the customers part (unwillingness to use new technology, no expertise, no trust in mobile devices and artificial intelligence) |
| Q12 | Our website allows to select a product/service meeting specific expectations and needs of customers (customize a product/service). |
| Q13 | We are fully prepared to serve digital customers (customers using mobile devices to do shopping or handle official matters etc.). |
| Q14 | In our company, we have positive return on investment. |
| Q15 | Profitability of our company is higher than that of competitors. |
| Q16 | Revenue increase in our company is higher than that of competitors. |
| variable | Scale summary: Mean=54.5209 St. deviation=8.40565 N valid:574 Cronbach's alpha: 0.690498 Standardized alpha: 0.707787 Average correlation between items: 0.143114 |
||||
|---|---|---|---|---|---|
| Mean when removed | Value when removed | St. deviation when removed | Total item corr. | Alpha when removed | |
| Q1 | 49.82753 | 69.95110 | 8.363677 | 0.013513 | 0.697062 |
| Q2 | 50.94599 | 59.76189 | 7.730582 | 0.341092 | 0.669848 |
| Q3 | 50.94599 | 70.05806 | 8.370070 | -0.077460 | 0.729879 |
| Q4 | 52.37282 | 58.43243 | 7.644111 | 0.405820 | 0.659885 |
| Q5 | 52.41115 | 60.86231 | 7.801430 | 0.309551 | 0.674342 |
| Q6 | 50.39373 | 60.60456 | 7.784893 | 0.516028 | 0.652622 |
| Q7 | 50.45645 | 59.81256 | 7.733858 | 0.598068 | 0.645295 |
| Q8 | 50.64808 | 60.18626 | 7.757980 | 0.516881 | 0.651386 |
| Q9 | 50.33972 | 60.98738 | 7.809442 | 0.541732 | 0.652296 |
| Q10 | 51.15505 | 66.17283 | 8.134668 | 0.118613 | 0.697552 |
| Q11 | 51.41463 | 66.90823 | 8.179745 | 0.115372 | 0.695450 |
| Q12 | 51.59756 | 60.08020 | 7.751142 | 0.338188 | 0.670184 |
| Q13 | 51.70557 | 58.88369 | 7.673571 | 0.435813 | 0.656255 |
| Q14 | 50.67073 | 66.79577 | 8.172868 | 0.147738 | 0.690865 |
| Q15 | 51.39199 | 66.36726 | 8.146610 | 0.260211 | 0.680796 |
| Q16 | 51.53659 | 66.45424 | 8.151947 | 0.251563 | 0.681431 |
| Statistics value | value p | Report | |
|---|---|---|---|
| Q1 | 0.44421 | p<0.01 | Based on the result of Kolmogorov-Smirnov test: p < ,01 at the significance level α = 0.05, the hypothesis of normality of distribution for all variables should be rejected. |
| Q2 | 0.24763 | p<0.01 | |
| Q3 | 0.25666 | p<0.01 | |
| Q4 | 0.35623 | p<0.01 | |
| Q5 | 0.35566 | p<0.01 | |
| Q6 | 0.26014 | p<0.01 | |
| Q7 | 0.24364 | p<0.01 | |
| Q8 | 0.23986 | p<0.01 | |
| Q9 | 0.26711 | p<0.01 | |
| Q10 | 0.23646 | p<0.01 | |
| Q11 | 0.17765 | p<0.01 | |
| Q12 | 0.18604 | p<0.01 | |
| Q13 | 0.16099 | p<0.01 | |
| Q14 | 0.25938 | p<0.01 | |
| Q15 | 0.34096 | p<0.01 | |
| Q16 | 0.32985 | p<0.01 |
| Variable | Mann-Whitney U test (with a continuity correction) Relative to the variable: question Indicated results are significant with p < 0.05000 |
||||||||
|---|---|---|---|---|---|---|---|---|---|
| Rank total Q1 | Rank total Q2 | U | Z | p | With corrections | p | N valid Q1 | N valid Q2 | |
| Answer (Likert scale) | 396007.00 | 263519.00 | 98494.00 | 11.79 | p<0.0001 | 13.38 | p<0.0001 | 574.00 | 574.00 |
| Dependent: Answer | ANOVA Kruskal-Wallis rank; Independent (grouping) variable: question Kruskal-Wallis test: H (2, N = 1722) = 279.9311 p = 0.000 | |||
|---|---|---|---|---|
| Code | N valid | Rank total | Average rank | |
| Q3 | 1 | 574 | 647578.00 | 1128.18 |
| Q4 | 2 | 574 | 420432.50 | 732.46 |
| Q5 | 3 | 574 | 415492.50 | 723.85 |
| Dependent: Likert scale (answers) |
Value p for multiple (two-way) comparisons; answer Independent (grouping) variable: question Kruskal-Wallis test: H (2, N = 1722) = 279.9311 p = 0.000 |
|||
| Q3 R:1128.2 | Q4 R:732.46 | Q5 R:723.85 | ||
| Q3 | p<0.0001 | p<0.0001 | ||
| Q4 | p<0.0001 | 1.0000 | ||
| Q5 | p<0.0001 | 1.0000 | ||
| Variable | Mann-Whitney U test (with a continuity correction) Relative to the variable: question Indicated results are significant with p < 0.05000 | ||||||||
|---|---|---|---|---|---|---|---|---|---|
| Rank total Q10 | Rank total Q11 | U | Z | p | With corrections | p | N valid Q10 | N valid Q11 | |
| Answer (Likert scale) | 351945.50 | 307580.50 | 142555.50 | 3.95 | 0.00 | 4.06 | p<0.0001 | 574.00 | 574.00 |
| Variable | Mann-Whitney U test (with a continuity correction) (Sheet2) Relative to the variable: question Indicated results are significant with p < 0.05000 | ||||||||
|---|---|---|---|---|---|---|---|---|---|
| Rank total Q12 | Rank total Q13 | U | Z | p | With corrections | p | N valid Q12 | N valid Q13 | |
| answer | 336138.50 | 323387.50 | 158362.50 | 1.14 | 0.26 | 1.16 | 0.25 | 574.00 | 574.00 |
| Dependent: answer | ANOVA Kruskal-Wallis rank; answer (Sheet2) Independent (grouping): question Kruskal-Wallis test: H (3, N = 2296) = 31.51557 p = 0.0000 | |||
|---|---|---|---|---|
| Code | N valid | Rank total | Average rank | |
| Q6 | 1 | 574 | 690001.50 | 1202.09 |
| Q7 | 2 | 574 | 654514.00 | 1140.27 |
| Q8 | 3 | 574 | 592927.50 | 1032.97 |
| Q9 | 4 | 574 | 699513.00 | 1218.66 |
| Dependent: answer | Value p for multiple (bilateral) comparisons; answer (Sheet2) Independent (grouping) variable: question Kruskal-Wallis test: H (3, N = 2296) = 31.51557 p = 0.0000 | |||
| Q6 R:1202.1 | Q7 R:1140.3 | Q8 R:1033.0 | Q9 R:1218.7 | |
| Q6 | 0.6848 | 0.0001 | 1.0000 | |
| Q7 | 0.6848 | 0.0367 | 0.2708 | |
| Q8 | 0.0001 | 0.0367 | p<0.0001 | |
| Q9 | 1.0000 | 0.2708 | p<0.0001 | |
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| Analysis type | Research tools |
| Analysis of statistical data Research Questions : RS 1 | |
| Comparative analysis of secondary data derived from reports by the European Commission, Eurostat and Statistics Poland | Deductive reasoning and structural analysis |
| Analysis of the survey results Research Question : RS 2 | |
| Preliminary analysis | |
| Assessment of the reliability of the survey questionnaire | Cronbach’s alpha test |
| Analysis of the distribution of normality of variables Verification of null research hypothesis H0 1 |
Kolmogorov-Smirnov test |
| Statistical analysis | |
| Verification of null research hypotheses | |
| H0 2; H0 4; H0 5 | Box-plots, Mann-Whitney U test |
| H0 3; H0 7 | Box-plots, ANOVA Kruskal-Wallis tests and Dunn’s post-hoc tests |
| H0 6 | Kendall's rank correlation coefficient/ MARSplines |
| Industry 4.0 tools | Medium-sized companies | Small companies | |
|---|---|---|---|
| Cloud services | 33.5% | 19.2% | |
| CRM | 7.9% | 3.8% | |
| Internet of things | In general | 31.8% | 14.9% |
| Customer service | 5.1% | 1.7% | |
| Artificial Intelligence | In general | 5.0% | 1.9% |
| Marketing and sale | 1.7% | 0.9% | |
| Variable | Kendall's tau correlation. BD removed in pairs. Marked correlation coefficients are significant with p <0.05000 |
||
| Q14 | Q15 | Q16 | |
| Q1 | 0,081956 | -0,067188 | -0,100356 |
| Q2 | 0,117383 | 0,129314 | 0,103223 |
| Q3 | 0,028331 | 0,016375 | -0,000893 |
| Q4 | 0,002843 | 0,097389 | 0,126442 |
| Q5 | 0,015420 | 0,051675 | 0,074143 |
| Q10 | -0,112189 | -0,070817 | -0,073550 |
| Q11 | -0,024304 | 0,030237 | 0,015573 |
| Q12 | -0,006976 | 0,072175 | 0,052036 |
| Q13 | 0,049448 | 0,068068 | 0,088144 |
| Characteristics | Dependent variable | ||
|---|---|---|---|
| Q14 | Q15 | Q16 | |
| Model equation | Q14 = 3,98687048471834e+000 - 1,07316216029357e-001*max(0; Q10-1,00000000000000e+000) + 2,72355316354401e-001*max(0; Q2-4,00000000000000e+000) | Q15 = 3,37263580519805e+000 - 1,18537225996519e-001*max(0; 4,00000000000000e+000-Q2) - 6,01555038434376e-002*max(0; Q10-1,00000000000000e+000) | Q16 = 3,51939935571921e+000 - 7,21101480713554e-002*max(0; 4,00000000000000e+000-Q2) + 5,94604120550734e-002*max(0; Q4-1,00000000000000e+000) - 6,01464024944235e-002*max(0; Q10-1,00000000000000e+000) - 1,08129596432386e-001*max(0; Q1-1,00000000000000e+000 |
| Penalty | 2.000000 | 2.000000 | 2.000000 |
| Threshold | 0.000500 | 0.000500 | 0.000500 |
| GCV error | 1.128497 | 0.662174 | 0.675047 |
| Predictors | Number of references to each predictor | ||
| Q14 | Q15 | Q16 | |
| Q1 | 0 | 0 | 1 |
| Q2 | 1 | 1 | 1 |
| Q3 | 0 | 0 | 0 |
| Q4 | 0 | 0 | 1 |
| Q5 | 0 | 0 | 0 |
| Q10 | 1 | 1 | 1 |
| Q11 | 0 | 0 | 0 |
| Q12 | 0 | 0 | 0 |
| Q13 | 0 | 0 | 0 |
| Null hypothesis | Method of verification | Result |
|---|---|---|
| H0 1 | Kolmogorov-Smirnov test | The null hypothesis was rejected, the alternative hypothesis was accepted |
| H0 2 | Mann-Whitney U test | The null hypothesis was rejected, the alternative hypothesis was accepted |
| H0 3 | ANOVA Kruskal-Wallis tests and Dunn’s post-hoc tests | The null hypothesis was rejected, the alternative hypothesis was accepted |
| H0 4 | Mann-Whitney U test | The null hypothesis was rejected, the alternative hypothesis was accepted |
| H0 5 | Mann-Whitney U test | The null hypothesis was accepted |
| H0 6 | Kendall's rank correlation coefficient/ MARSplines | Ambiguous results |
| H0 7 | ANOVA Kruskal-Wallis tests and Dunn’s post-hoc tests | The null hypothesis was rejected, the alternative hypothesis was accepted |
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