**6.3 Integrating data-driven performance evaluation into the algorithm management design**

Using driver ratings and approval thresholds, businesses can test drivers on a wide scale. In particular, driver ratings may appear to be a valid assessment tool because customer loyalty is a significant indicator of service performance and human service provider efficiency. Using only the monitored output data in assessing staff, though, has uncovered several problems that may arise if one depends too heavily on quantified metrics without further analysis of their meanings and complexities. Consistent with previous studies on letter-grading schemes or numerical appraisal of teaching skills [11], several random variables beyond drivers' reach affect the way passengers rate drivers. The effectiveness and accuracy of the averaged group assessment, rather than the in-depth holistic review carried out by a human manager or peer, is also at issue. As P18 put it, "you are at the hands of unknown strangers, in [his other work] you are judged by people you meet." Our research also reveals the pitfalls of following a 5-star rating system shared with web goods, content, or business ratings for human employees. Drivers felt that passengers rated conservatively as they did in online reviews; however, interviews with passengers suggest that they are more lenient and positive than drivers think. This misunderstanding indicates that a 5-star ranking metaphor and a heading may have contributed to incorrect comparisons. Finally, the long-term motivational impact of the ranking is still at issue. As the driver ratings were weighted over several journeys, the effect of one positive or negative ride was reduced, and the drivers in our study were less susceptible to changes in their ratings until they were above the minimum threshold.

Effective management offers working procedures and enables improvisation in response to changes and exceptions [12]. On the other hand, task algorithms have penalized all driver rejections of assignments, even though individual drivers had valid motives and situations for doing so. While we have not seen any significant problems with this lack of versatility in our algorithmic analysis assignment, it poses an open challenge in building flexibility in algorithmic management.

An examination is optional in most online rating programs, and many even miss the process. In the ride-sharing service, both riders were urged to score their service experience, and most of them did. Being held responsible for all communications, the drivers were well aware of this external assessment's nature. Trying to offer adequate care with all customer encounters could pose psychological stress to staff. Besides, as comprehensive research on extrinsic incentives' effect on intrinsic motivation indicates, an external device may undermine the innate incentive drivers may have and alter the sense they assign to their behavior. From the passengers' point of view, the uncertainty of the provider's motivation for friendliness and good service risks making the provider's relationship more superficial and perfunctory.

#### **6.4 Designing algorithmic management that supports online forum**

Our study found that online forums have been the primary place where drivers socialize, ask questions about each other, and share information and strategies.

#### *Evaluation of Algorithmic Management of Digital Work Platform in Developing Countries DOI: http://dx.doi.org/10.5772/intechopen.94524*

In most research on intelligent systems' sensory and mental models, the focus was on individual sensemaking [13–15]. Our research indicates that social sensemaking is another critical task that needs to be correctly understood and endorsed if intelligent systems are effectively implemented. Social sensemaking events at the driver's forums adopted "fragmented social sensemaking" [10]. Many involved contributors have no overarching authority to put together various thoughts and narratives into a cohesive plot. This kind of sensemaking was useful in addressing rating enhancement techniques. There were no accurate or incorrect responses, and employees' knowledge and learned and improvised techniques played a critical role. On the other hand, fractured social sensemaking fell short on topics where only an authority figure had the correct details. This highlights possibilities for creating organized online social sensemaking algorithmic features where individuals can draw on each other's expertise.
