An Innovative Tool to Measure Employee Performance through Customer Satisfaction: Pilot Research Using eWOM, VR, and AR Technologies
Abstract
:1. Introduction
- Concentrated effort strategy;
- Differentiation strategy through products, services, outlets, and prices [3];
- Strategy of global domination through costs.
- Online commerce;
- Package delivery services;
- Automotive industry.
- They are the first measurement tools that simultaneously take into consideration: customer satisfaction, employee performance, and company performance.
- The implementation methodology used new electronics technologies and information systems, as follows: augmented reality (AR), virtual reality (VR) Spectacles VR-BOX v2.0, electronic word-of-mouth (eWOM), VR glasses, chat, platform Warp Studio, OCS (Online Comments System) platform and Kahoot platform.
- There are well-known tools for measuring service/product quality, customer satisfaction (e.g., SERVQUAL), and continuous company improvement (e.g., Six Sigma, Lean Six Sigma, EFQM Excellence Model of European Foundation Quality Model). These tools work separately from only one direction and from the QMS (Quality Management System), not as an interface of customer satisfaction—employee performance—company performance as Spc and ITA methodology does.
- Our paper specifically corresponds to the new trends in the digital era and focuses on how information technologies, electronic multimedia, and computer science change business models and significantly affect companies’ performance. The rapid penetration of information technologies brings new opportunities for innovation, continuously improving and increasing efficiency and identifying key applications of information technology in practice. In this context, our research contributes to investigating the application of such technologies and information systems as those mentioned above in the business area.
- (1)
- Decreasing the number of NRR (Negative Response Rate) followed by decreasing the number of dissatisfied customers and the number of dissatisfied employees;
- (2)
- Total cost reduction;
- (3)
- Waste reduction through economic efficiency of the yield of production factors (Eeypf) and economic efficiency on the consumption of production factors (Eecpf);
- (4)
- Continuous improvement of the management process;
- (5)
- Economic performance measured by turnover and profit.
2. Literature Review
2.1. Six Sigma and Lean Six Sigma
2.2. Customer Satisfaction—Short Evolution of Measurement Methods and Concepts
- Customer satisfaction is an affective or cognitive response that can vary in intensity;
- The response focuses on a specific element: product, expectations, services, etc.;
- The answer is specific only to a specific period: after the purchasing experience, after consumption, etc.
2.3. Interface Quality—Employees—Customers—Company Performance
3. Materials and Methods
- Regarding the customer satisfaction measurement tool, a possibility of its adjustments and adaptations must exist in a competitive company [36];
- By ensuring the important interface quality—employees—customers—company performance for a competitive company, the education of the employee can be formal, informal, or non-formal [59].
- 32 employees from an e-commerce company;
- 67 employees from a services company (parcel delivery);
- 22 employees from an automotive industry company.
- Spc = the Spc indicator;
- WmL = average labor productivity;
- Maps = weighted arithmetic average of customer satisfaction;
- Cha = salary expenses per employee per hour (in Euro);
- t = average time to solve a specific task;
- Σc = total amount of contacts (employee effort).
- For e-commerce, the WmL represents the average number of direct contacts resolved (customer—employee) per hour per employee by chat or/and phone;
- For parcel delivery services, the WmL represents the average number of packages delivered (voluminous or simple) per hour per employee;
- For the automotive industry, the WmL represents the average time to dismantle or deliver a part/piece.
- For values 0.00–0.09, the Spc indicator shows poor employee efficiency;
- For values 0.10–0.19, it indicates a medium efficiency;
- For values 0.20–0.29, the Spc indicates a good efficiency of the employees;
- For values 0.30–0.39, the significance of the Spc is very good;
- Over or equal to 0.40, the Spc shows excellent employee efficiency.
- For electronic commerce, the OCS (online comment system) platform of the company was used by the authors together with the company assistant;
- For the package delivery services, the authors used AR technology and VR Spectacles VR-BOX v 2.0 and VR glasses to optimize the storage and transport vehicle spaces;
- For the automotive industry, VR technology and Warp Studio Platform were used for initiating the employee.
4. Results
5. Discussion
- Provide a unique learning and knowledge exchange environment;
- Provide opportunities for group interactions engaged in learning;
- Improve communication skills (so that trainees can easily transfer course knowledge to real-life situations);
- Support creativity, exploration, and identity development.
- H1: A growth and development program requires continuous improvements related, adapted, and updated to the period of time in which it is applied;
- H2: Performance evaluation systems require innovative adjustments by including elements from other sectors.
6. Conclusions
- Increasing labor productivity, followed by an increase in the number of contacts for an employee.
- Improving the cognitive process of employees within the company, which was directly reflected in the improvement of the company’s economic and financial indicators.
- Improving the relationship between employees and customers, leading to increased satisfaction.
- Reorganization of the employee program resulting in increased staff efficiency.
- Better control over the operating parameters of each employee and the entire sector by introducing an SIM and SIAR program.
- The applied research presented in this paper reveals real situations at a national level in two sectors, one secondary and one tertiary; the latter being the most developed, not only at a national but also at a global level.
- The Spc indicator and ITA methodology introduced and implemented by the authors do not intend to eliminate the methods already used at the company level.
- The Spc indicator and ITA methodology introduced and implemented by the authors show that some aspects need to be continuously improved to increase the company’s economic performance, which is often determined in economic terms [6].
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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Field of Research | Author and Publication Year |
---|---|
Distribution channels | Andaleeb, 1992 [47] |
Anderson and Narus, 1990 [48] | |
Anderson and Weitz, 1989 [49] Shurr and Ozanne, 1985 [50] | |
Consumer markets | Fletcher and Peters, 1997 [51] |
Gurviez, 1996 [52] | |
Services | Crosby, Evans, and Cowles, 1990 [53] |
Grayson and Ambler, 1999 [54] | |
Moorman, Zaltman, and Deshpandé, 1992 [55] | |
Moorman, Deshpandé, and Zaltman, 1993 [56] |
Symbol from Spc Indicator Formula | Variable Name and UM | Company’ Sector | ||
---|---|---|---|---|
E-Commerce (Pilot Research) | Services | Industry | ||
Employee performance assessment system based on customer satisfaction | Legend for Spc values and interpretation: | |||
0.0–0.09 | Weak | |||
0.10–0.19 | Medium | |||
0.20–0.29 | Good | |||
0.30–0.39 | Very good | |||
≥0.40 | Excellent | |||
WmL | Average labor productivity | Average number of contacts resolved (chat/phone)/hour/employee | Average number of packages (voluminous/simple) delivered/hour/employee | Average number of parts (dismembered/delivered)/hour/employee |
Maps | Weighted arithmetic average of satisfaction | E-mail to the customer’s address with 5-point Likert scale questionnaire (1—dissatisfied ft... 5—satisfied ft) completed by the customer after contact with the employee | ||
Cha | Salary expenses/employee/hour (euro) | |||
t | Average time to solve a task | Average time to resolve a contact with the customer (min) | Average time to deliver a package | Average time to dismantle/deliver a part |
Σc | Total amount of contacts (employee effort) | Contacts taken over (telephone and chat) | Collets delivered | Delivered/disassembled parts |
Method Used for Implementing Spc | ITA Methodology (Initiation—Testing—Application) with the Following Steps for Implementing: | |||
Step 1: Initiating: tools for preparation | The OCS (Online Comments System) platform used by the company | AR technology, Virtual Reality Spectacles VR-BOX v 2.0 | VR technology: Platform Warp Studio (https://www.warpvr.com/ access on 1 June 2020) | |
Step 2: Testing method for employee | Mystery shopper and focus group | Mystery shopper, testing through contest on Kahoot platform, interview | Mystery shopper, testing through contest on Kahoot platform | |
Step 3: Application (Program used) | SIM (Spc Indicator—ITA method with Mystery Shopper) | SIAR (Spc Indicator—ITA method with AR technology) | SIAR (Spc Indicator—ITA method with VR technology) | |
The companies KPIs were used: the turnover, the profit, the total costs (all in Euros), the number of employees, the Eeypf—Economic efficiency of the yield of production factors (the value must be over 1 unit), the Eecpf—Economic efficiency on the consumption of production factors (the value must be under 1 unit), Rate of return (in %). | ||||
Other Information | ||||
Number of employees in study | 32 | 67 | 22 | |
Initial moment (before implementing Spc)—M0 | December 2018 | July 2020 | April 2020 | |
Implementation period (after implementing Spc) M1/M2/M3 | January (M1)—February (M2)—March (M3) 2019 | August (M1)—September (M2) 2020 | May (M1)—June (M2) 2020 | |
Customer service element used for each sector | NRR—Negative Response Rate | Complaint–receiving systems (free phone lines) | Complaint reception systems (forms) | |
Employee—client type of contact/communication | eWOM (electronic word-of-mouth) (chat and phone) | Face to face/WOM—Word-of-mouth | Face to face/WOM—Word-of-mouth |
Moment | Contacts Taken | Hours Worked/ Month | Cost/Hour /Employee (euro) | Maps | t | WmL | Σc | Σc/h | Average Value of Spc and Interpretation | ||
---|---|---|---|---|---|---|---|---|---|---|---|
Chat | Phone | ||||||||||
E-commerce (32 employees) | |||||||||||
M0 | 109 | 161.1 | 125.1 | 4.05 | 2.87 | 8.45 | 3.50 | 12,223 | 97.7 | 0.120 | Medium |
M1 | 116.9 | 275 | 129.2 | 4.05 | 3.72 | 7.46 | 3.00 | 12,557 | 97.3 | 0.158 | Medium |
M2 | 100.5 | 377 | 128.1 | 4.05 | 3.62 | 7.73 | 3.75 | 15,281 | 119.4 | 0.213 | Good |
M3 | 112.5 | 334 | 115.5 | 4.05 | 3.71 | 7.55 | 3.85 | 14,292 | 124.3 | 0.218 | Good |
Services (67 employees) | |||||||||||
M0 | - | - | 138.0 | 3.25 | 3.38 | 6.86 | 8.98 | 1206 | 9.00 | 0.105 | Medium |
M1 | - | - | 155.7 | 3.25 | 3.45 | 6.60 | 9.20 | 1422 | 9.20 | 0.132 | Medium |
M2 | - | - | 162.3 | 3.25 | 3.27 | 6.40 | 9.47 | 1535 | 9.46 | 0.140 | Medium |
Industry (22 employees) | |||||||||||
M0 | - | - | 175.5 | 4.15 | 3.07 | 7.21 | 8.38 | 1467 | 8.77 | 0.086 | Weak |
M1 | - | - | 173.9 | 4.15 | 3.44 | 6.95 | 8.70 | 1513 | 8.77 | 0.102 | Medium |
M2 | - | - | 175.0 | 4.15 | 3.63 | 6.41 | 9.43 | 1646 | 8.73 | 0.130 | Medium |
Performance Indicator | E-Commerce | Services | Industry | |||||||
---|---|---|---|---|---|---|---|---|---|---|
Before | After | Before | After | Before | After | |||||
M0 | M1 | M2 | M3 | M0 | M1 | M2 | M0 | M1 | M3 | |
Turnover (€) | 97,470 | 96,248 | 101,744 | 97,470 | 106,988 | 44,630 | 45,728 | 1,305,669 | 1,286,323 | 1,299,307 |
Profit (€) | 13,182 | 12,967 | 22,123 | 13,182 | 29,889 | 5219 | 5966 | 21,059 | 23,763 | 25,853 |
Total costs (€) | 84,288 | 83,281 | 79,621 | 84,288 | 77,099 | 39,411 | 39,762 | 1,284,610 | 1,262,560 | 1,273,454 |
Number of employees | 39 | 39 | 41 | 39 | 41 | 88 | 88 | 27 | 27 | 27 |
Eeypf 1 | 1.16 | 1.16 | 1.28 | 1.16 | 1.39 | 1.13 | 1.15 | 1.02 | 1.02 | 1.02 |
Eecpf 2 | 0.86 | 0.87 | 0.78 | 0.86 | 0.72 | 0.88 | 0.87 | 0.98 | 0.98 | 0.98 |
Rate of return % | 15.64 | 15.57 | 27.79 | 15.64 | 38.77 | 13.24 | 15.00 | 1.64 | 1.88 | 2.03 |
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Legman, I.-D.; Gabor, M.R.; Kardos, M. An Innovative Tool to Measure Employee Performance through Customer Satisfaction: Pilot Research Using eWOM, VR, and AR Technologies. Electronics 2023, 12, 1158. https://doi.org/10.3390/electronics12051158
Legman I-D, Gabor MR, Kardos M. An Innovative Tool to Measure Employee Performance through Customer Satisfaction: Pilot Research Using eWOM, VR, and AR Technologies. Electronics. 2023; 12(5):1158. https://doi.org/10.3390/electronics12051158
Chicago/Turabian StyleLegman, Ioan-David, Manuela Rozalia Gabor, and Mihaela Kardos. 2023. "An Innovative Tool to Measure Employee Performance through Customer Satisfaction: Pilot Research Using eWOM, VR, and AR Technologies" Electronics 12, no. 5: 1158. https://doi.org/10.3390/electronics12051158
APA StyleLegman, I. -D., Gabor, M. R., & Kardos, M. (2023). An Innovative Tool to Measure Employee Performance through Customer Satisfaction: Pilot Research Using eWOM, VR, and AR Technologies. Electronics, 12(5), 1158. https://doi.org/10.3390/electronics12051158